Scientific Data Research Articles

The Curve Fitting Problem, Data Validation, and Inductive Generalization in Machine Learning

AbstractAris Spanos and Deborah Mayo’s error-statistical approach to statistical modeling and inference adopts the reliability of inductive inference as a primary criterion for statistical model and estimator selection (e.g., curve fitting). In this paper, we expand the error-statistical approach’s adoption of reliable inductive inference by scrutinizing the epistemic legitimacy of contemporary techniques leveraged in data science. We argue that data validation and testing potentially provides a direct, measurable method of evaluating evidence for reliable inductive inferences in cases where the error-statistical approach is not easily applied, and conclude with an exploration of core methodological foils to the reliability of inductive inference revealed by this argument.

Taxonomic Data Objects for Communicating the Meaning of Species Names

A central problem in biodiversity data science remains the inability to precisely aggregate observations that originate from the same species. Current approaches still rely heavily on the ‘Genus species’ pair of Linnaean taxonomy to label and group data. However, such binomial species names do not alone contain enough information to distinguish variation in a name’s conceptual usage (i.e., meaning) across time, place, or investigator. This “species name-to-meaning” problem is well known, but no robust and scalable solutions yet exist (Berendsohn 1995Bisby 2000, Sutherland et al. 2000, Page 2007, Franz and Sterner 2018, Upham et al. 2021, Sterner et al. 2023, Sterner et al. 2020, Beach et al. 1993). The problem is widespread especially for well-studied groups like mammals, for which 45% more species are now recognized than 30 years ago, including many species splits and rearrangements (Burgin et al. 2018, Mammal Diversity Database 2024). To address this problem, we here propose to digitally package and sign the relevant taxonomic data associated with a given species name usage to form a ‘Taxonomic Data Object’ (TDO). These TDOs are conceptually similar to 'secundus' references (i.e., species name sec. author, Berendsohn 1995) but differ in being machine readable and thus operational from the perspective of high-throughput data science. TDOs aim to move from analog secundus references, which require a human to track meaning by reading the cited article, to a digital and machine-actionable taxonomic reference. Versioned TDOs that are digitally signed using hash algorithms (e.g., md5 or sha256, see Elliott et al. 2023) will allow for precisely communicating, with verified data provenance from sender to receiver, certain aspects of what a species name means according to a given authority at a given time. Example TDO contents include DarwinCore terms (e.g., scientificName, namePublishedIn, nameAccordingTo, nomenclaturalStatus (Darwin Core Maintenance Group 2021)) as well as meaning-rich digital assets like geographic range maps (e.g., GeoJSON format), exemplar DNA sequences (e.g., FASTA format or National Center for Biotechnology Information (NCBI) accession number), holotype specimen information (e.g., catalog number, type locality coordinates), and taxonomic treatment texts (including material citations, e.g., as digitized and extracted by Plazi TreatmentBank, Agosti and Egloff 2009; see Fig. 1). We discuss pilot examples comparing global bat species according to the v1.2 vs. v1.11 taxonomies of the Mammal Diversity Database (Sep 2020 vs. Apr 2023), showing how TDOs enable the reliable tracking of taxonomic meaning for the 63 bat species affected by splits during this period. We posit that widespread use of TDOs will enable the traceable exchange of taxonomic information across a variety of existing platforms, providing a path for accurate species-level data aggregation at global scales, at least for well-studied taxa.

No Evolution Without Revolution: Historical Revelations for LIS Education

As the field evolves and adapts to emerging technologies and societal changes, the rich historical context and radical changes that have shaped libraries and information systems risks being overshadowed. This SIG panel presentation will feature presentations ranging from understanding the role of caucuses in the LIS field, using creative storytelling to illuminate LIS history, and how AI will impact our ability to tell, know, and make history. Following the presentations, we expect to have a conversation about how we preserve and share LIS history in the face of technological change. National Associations of Librarians of Color Provides Historical Context to Teach Social Justice Work - Long Before DEI and social justice were integrated into statements, core principles, standards, or competencies for LIS education, there were efforts conducted by BIPOC library leaders who moved the needle in the profession by establishing professional associations that represented their communities. This presentation makes the connection between diversity efforts in LIS history and LIS pedagogy, by proposing the use of the specific historical context of social movements to substantiate and inform the social justice work that current LIS graduates will encounter. Demystifying the Past to Examine the Present and Shape the Future: Historical Research and Creative Storytelling in LIS Education - Ely-Ledesma Unpacking the complicated history of libraries in the United States, and recognizing historical threads that connect past to present, is vital as the profession continually adapts to emerging technologies and societal changes. When considering implementing historical perspectives into LIS education, we must ask a basic question: How can we infuse historical perspectives into LIS courses in an effective way? Historical research and creative storytelling are one way to address this question. To this end, I propose a three-step process for a project suitable for foundational courses or courses on library history. Teaching the History and the Evolution of the Information and Knowledge Profession - Hawamdeh According to Marcus Garvey “A person without the knowledge of their past history, origin, and culture is like a tree without roots." Understanding the LIS history, evolution and the radical changes is a key to the continued transformation of the information and knowledge profession. The continued expansion, evolution, and the emergence of concepts such as knowledge management, data science and generative AI are raising questions like how these concepts are related to LIS, how can they be woven into LIS curriculum, and how historical perspectives can be used to shape the future of the information and knowledge profession.

Big Research Data Management Needs of Researchers at a Research- Intensive University - A Qualitative Study

Big Research Data Management (BRDM) infrastructure is a complex socio-technical system. The design and provision of effective BRDM services at research universities require a multipronged examination of individual, social, technical, and larger contextual (i.e., campus, state, and national context) aspects of the BRDM infrastructure needs and uses of their users. Although there is a significant body of literature on BRD already, an in-depth, theory-driven examination of researchers’ needs for BRDM services on university campuses and the challenges and hurdles they face in using and managing BRD is lacking. Furthermore, there is a dearth of research on university administrators’ motivation for providing BRD services on their campuses and the hurdles and barriers they face in providing those services.This study aims to contribute to the literature by investigating the BRD-related needs of researchers from different fields and the barriers and challenges to designing and providing such support at a research university. The ongoing Health Data Science Initiative (HDSI) of Florida State University and user interviews are used as the data sources of this study. The study is guided by activity theory to investigate the complex structure of activities and factors that make BRDM infrastructure successful on university campuses.When completed, the study will inform the design of BRDM infrastructure and services on university campuses by providing an evidence base for the perspectives and needs of BRD creators, users, curators, and policymakers. In particular, by understanding the BRDM requirements of researchers, university administrators can provide effective and user-centered BRDM solutions to them.

Clinico-Epidemiological Profile and Outcome of Acute Poisoning Patients admitted to Intensive Care Unit in A Tertiary Level Private Hospital in Bangladesh

Background: Acute poisoning is a prevalent health issue necessitating Intensive Care Unit (ICU) admission in developing countries. This study evaluates the socio-demographic characteristics, clinical parameters, and outcomes of acute poisoning patients admitted to the ICU in a tertiary level private hospital in Bangladesh. Method: This retrospective cohort study was conducted at tertiary care private hospital in Narayanganj, Bangladesh. Data was collected from ICU medical records from January 2023 to April 2024, enrolling a total of 57 patients aged 18 years or more who presented with acute poisoning. Data analysis was performed using Stata (Statistical Software for Data Science) 17.0(p < 0.05) Results: Out of 57 patients, 52.63% were females, with mean age of 27.84 years. Suicidal intent accounted for 84.21% of cases, and the primary reasons for poisoning included marital (61.40%) and familial disharmony (15.79%). The predominant type of poisoning was due to sedatives (17.54%) followed by aluminium phosphide (14.04%), and stupefying agents (14.04%). Aluminium phosphide poisoning had a 100% fatality rate, while sedatives and several other agents had 100% recovery rate. Statistical analysis showed a significant association between the type of poison and the final outcome (χ2(15) = 38.7996, p = 0.001). Conclusion: The study highlights the prevalence of intentional poisoning among young adults, especially females, with sedatives, aluminium phosphide, and stupefying agents being the most common. The high mortality rate from aluminium phosphide underscores the need for strict regulations and public awareness to control access to these substances. Bangladesh Crit Care J September 2024; 12 (2): 89-95

Exploring the relationship between frugivorous birds and fruit trees in urban parks using citizen science data

Exploring the relationship between frugivorous birds and fruit trees in urban parks using citizen science data

PROBLEMS OF CHOOSING A METHOD OF DENTAL TREATMENT OF TEETH AFTER ENDODONTIC INTERVENTION

The optimal way to restore the anatomical structure of teeth after endodontic intervention is a controversial topic. Teeth after endodontic intervention have different properties compared to intact living teeth. Changes in these properties are associated with volumetric loss of hard tissues, caries, final preparation of the cavity taking into account access to endodontic treatment. Choosing the optimal method of dental treatment of teeth requires compliance with many factors, such as: prevention of infection penetration into root canals, restoration of tooth contacts, restoration of chewing functions, protection against further carious and non-carious destruction, restoration of tooth aesthetics. Dentists are now more than ever aware of the interdependence of the endodontic and restorative aspects of dental treatment and how much this will affect achieving the best long-term outcome. Controversies of the clinical relevance of endodontic and restorative treatment choice issues are mostly unanswered based on clinical data and scientific evidence. The modern approach to tooth restoration after endodontic intervention is an important topic. To improve clinical outcomes, it is important to determine the effectiveness of treatment, the importance of preserving tooth structure, the choice of treatment method with restorative materials, and the integration of digital dentistry to improve diagnosis and treatment principles. Research rationale. The purpose of this study is to find and use literature data on the effectiveness of modern methods of dental treatment after endodontic intervention in Ukraine. Materials and methods. Scientific data from a review and systematic analysis of the literature were used. Materials were searched using the Google Scholar, PubMed, Google Scholar databases and open sources of the World Health Organization, the Ministry of Health of Ukraine and other government web portals of Ukraine. Results, Discussion. After conducting a literature analysis to compare the effectiveness of using cast metal inserts and fiberglass posts, we can come to the conclusions that retrospective studies on the relationship between successful restorations and such factors as the type of tooth, the volume of residual hard tissues, the number of occlusal contacts, the type of the final restoration and the position of the tooth in the dental arch are the main criteria for choosing a treatment method. A controversial choice is that metal abutments are associated with a higher risk of root fracture, their manufacture requires laboratory techniques, while the use of fiberglass posts is associated with a higher risk of decementation, and overloading of fiberglass posts leads to their fractures. Conclusions. Decision-making and the choice of methods of dental treatment after endodontic intervention remain difficult. However, the interdependence of endodontic treatment and restoration of the crown part of the tooth is clearly established. Physicians must consider both aspects of treatment equally to ensure the best possible outcomes for their patients. The use of digital scanning enables an accurate volumetric assessment of the residual hard tissues of the tooth, which can be used to provide tangible qualitative results of the analysis and decision-making with the choice of treatment method. The choice of treatment method is not defined in a single protocol and requires further careful study with new experimental developments, based on the latest technologies of world leaders in dentistry.

Examining Bhutanese Science Teachers’ Epistemic Views of Scientific Inquiry

AbstractScientific inquiry is regarded as the bedrock of science education in Bhutan. Bhutanese science teachers, for example, are increasingly required to possess accurate and deep epistemic views of scientific inquiry. Hence, this cross-sectional study was carried out to examine Bhutanese science teachers’ epistemic views of scientific inquiry. The study recruited 301 science teachers using convenience and snowball sampling procedures. Data was collected using Views About Scientific Inquiry (VASI) questionnaire administered through an online survey mode and analysed using descriptive statistics and inferential statistical methods. Findings from this study revealed Bhutanese science teachers as being ignorant of epistemic aspects related to questions and hypotheses, procedures of investigations, results, and procedures of investigations, scientific data and scientific evidence, and scientific explanations and scientific theories. The independent sample t-test revealed no significant difference between Bhutanese male and female science teachers’ epistemic views of scientific inquiry (p > .05). The one-way ANOVA revealed significant differences amongst Bhutanese science teachers’ epistemic views of scientific inquiry based on academic qualification (p < .05). The Tukey HSD post hoc test, however, showed the differences existing only between science teachers with master’s degree and certificate qualification in favour of the former (p < .05). The three-way ANOVA revealed Bhutanese science teachers’ epistemic views of scientific inquiry as being independent of individual and interaction effects of school type, teaching subject, and teaching experience (p > .05).

Modeling Enzyme Kinetics: Current Challenges and Future Perspectives for Biocatalysis.

Biocatalysis is becoming a data science. High-throughput experimentation generates a rapidly increasing stream of biocatalytic data, which is the raw material for mechanistic and novel data-driven modeling approaches for the predictive design of improved biocatalysts and novel bioprocesses. The holistic and molecular understanding of enzymatic reaction systems will enable us to identify and overcome kinetic bottlenecks and shift the thermodynamics of a reaction. The full characterization and modeling of reaction systems is a community effort; therefore, published methods and results should be findable, accessible, interoperable, and reusable (FAIR), which is achieved by developing standardized data exchange formats, by a complete and reproducible documentation of experimentation, by collaborative platforms for developing sustainable software and for analyzing data, and by repositories for publishing results together with raw data. The FAIRification of biocatalysis is a prerequisite to developing highly automated laboratory infrastructures that improve the reproducibility of scientific results and reduce the time and costs required to develop novel synthesis routes.

Cow Dung Liquid Mulch Improves Maize Yields: Beneficial Microorganisms Are Enriched and Environmental Risks Are Reduced and Nutrient Cycling Is Promoted

Cow dung liquid mulch (CDLM), which uses cow dung as a raw material, has a good degradability and is a potential alternative to traditional plastic agricultural mulch, but there is a lack of research on the effects of CDLM on rhizosphere soil physicochemical properties, rhizosphere soil microbial functions, and crop yields. In this study, the link between maize yield, environmental factors, and functional genes as well as the responses of microbial community functions to CDLM and polyethylene mulch (PE) were studied using metagenomic sequencing. Functional annotation was also performed on clusters of orthologous groups of proteins, the Kyoto Encyclopedia of Genes and Genomes, and carbohydrate-active enzyme sequencing data. The results showed that CDLM significantly increased maize yield by 30.9% compared to CK while maintaining lower soil microplastic levels. CDLM promotes the enrichment of beneficial microorganisms such as Mycolicibacterium and Pseudomonas. The relative abundance of functional genes related to microbial metabolism, soil element cycling pathways, and organic matter degradation was significantly higher in CDLM than in CK. Microbial functional genes were positively correlated with maize yield and environmental factors such as soil nutrients. These results suggested that CDLM can improve maize yield by enriching beneficial microorganisms, reducing rhizosphere soil environmental risks, and enhancing rhizosphere soil microbial function. Rhizosphere soil nutrients and microbial functional genes together mediated the positive response of maize yield to CDLM. This study can provide a scientific basis and data support for the safe use of mulch in the future.

EVALUATION OF STUDENTS' TRAINING LEVEL IN THE ELECTIVE DISCIPLINE "QUALITY SYSTEMS IN PHARMACY"

The pharmaceutical industry is rapidly developing and implementing new innovative approaches and legal regulation of the quality management system of medicinal products, which includes a set of methods, processes and resources that are necessary for quality management. Therefore, the study by students of the specialty 226 "Pharmacy, industrial pharmacy" of the elective discipline "Quality systems in pharmacy" is an important area of professional training of a qualified specialist who will master the methodology of quality management, normative-legislative and organizational-economic aspects of quality control of medicinal products at pharmaceutical enterprises. Training of domestic students in the field of drug technology is an important direction of pharmaceutical education today. The main tasks of studying the elective discipline "Quality Systems in Pharmacy" are: formation of students of higher education in general knowledge about the quality indicators of medicinal products according to the stage of their life cycle by fulfilling the requirements of proper pharmaceutical practices and developing documentation in accordance with their requirements; formation of practical skills; raising the level of general and scientific development of students of higher education, forming their outlook and perspective as modern qualified specialists in the field of pharmacy. The purpose of the work was to study the assessment of the level of training of domestic students in the elective discipline "Quality Systems in Pharmacy". Materials and methods. We used an empirical research method (questionnaire). Questionnaire was a key research method, as it allows to get answers from the student audience regarding the organization of the educational process. A survey was conducted to assess the level of preparation of domestic students of the 5th year of the Faculty of Pharmacy who completed the study of the selective discipline "Quality Systems in Pharmacy". 50 full-time students and 2 distance learning students took part in the survey. Out of all the respondents, only one studies on budget forms of education. Research results. According to the curriculum, the elective discipline "Quality Systems in Pharmacy" at the Faculty of Pharmacy of IFNMU is studied in the V course in the IX semester, at the stage when students have already acquired basic knowledge of pharmaceutical disciplines. The discipline is chosen by already formed specialists who possess a large stock of theoretical knowledge and practical skills and are motivated to study a new subject, so it remains for the teacher to systematize information for the proper conduct of the discipline study course. 3 ECTS credits are provided for the study of the discipline in the curriculum. The discipline includes 20 hours of lectures, 30 hours of practical classes, 40 hours of independent student work and ends with a module. Lecture and practical material taught at the level of modern scientific and practical data with the aim of forming students' program results. We conducted an analysis of problems in the organization of the educational process for students of the Faculty of Pharmacy of the Ivano-Frankivsk National Medical University during full-time education. The success of implementing the selective discipline "Quality Systems in Pharmacy" and ensuring a high level of training depends primarily on the quality of the work of scientific and pedagogical workers.

High-resolution observations of the ocean upper layer south of Cape St. Vincent, the western northern margin of the Gulf of Cádiz

Abstract. This article presents an Eulerian physical and biogeochemical dataset from the Iberian Margin Cape St. Vincent Ocean observatory (IbMa-CSV), a facility of the European Multidisciplinary Seafloor and water column Observatory European Research Infrastructure Consortium (EMSO-ERIC), located 10 nautical miles south of Cape St. Vincent (Portugal), the southwest tip of the Iberian Peninsula and western limit of the northern margin of the Gulf of Cádiz (GoC). The observatory was installed on the shelf break, and the data time series spans 4 months for most of the variables. The upper 150 m were sampled intensively with a wave-powered vertical profiler at an average rate of 4.5 profiles per hour recording at 2 Hz when ascending at an approximate velocity of 0.2 m s−1 and 10 Hz when descending at a variable velocity. The vertical resolution was always higher than 0.2 m. Measured channels were conductivity, temperature, pressure, chlorophyll a, dissolved O2 concentration, and turbidity. Derived channels are sea pressure, depth, salinity, speed of sound, specific conductivity, dissolved O2 saturation, density anomaly, spiciness, and Brunt–Väisälä frequency. The acquired dataset includes the flow velocity and direction along the water column, taken from an upward-looking 300 kHz acoustic Doppler current profiler (ADCP) recorded every hour for 3 m depth bins extending the same depth range of the vertical profiler. A standard quality-control scheme was applied to the dataset. The dataset is preserved for multiple use and is accessible in the Sea Open Scientific Data Publication (SEANOE) repository via the following address: https://doi.org/10.17882/94769 (Rautenbach et al., 2022).

What does e-invoice data bring to SNA and real-time economy?

This paper explores the potential of electronic invoice data to enhance the System of National Accounts (SNA) and facilitate a Real-Time Economy (RTE). The rise of data science and advancements in information and communication technologies have increased the use of big data in economic statistics. E-invoice data is being digitized in Europe to detect VAT fraud, but it also contains a vast amount of information on economic entities that make up the SNA. This study focuses on integrating electronic accounting information to improve the coverage, granularity, and update speed of SNA. The paper examines the concept of RTE, which emphasizes real-time data processing and automation, particularly in Estonia and Finland. It also highlights the benefits and challenges of using invoice data for economic statistics, including issues related to data storage formats, legislative systems, and the coordination of data linkages. The research demonstrates invoice data’s theoretical and practical applications for constructing Input–Output Tables (IOTs) and monitoring financial situations. Despite the technical and institutional hurdles, the study suggests integrating invoice data can significantly transform economic statistics.

TeraHeap: Exploiting Flash Storage for Mitigating DRAM Pressure in Managed Big Data Frameworks

Big data analytics frameworks, such as Spark and Giraph, need to process and cache massive datasets that do not always fit on the managed heap. Therefore, frameworks temporarily move long-lived objects outside the heap (off-heap) on a fast storage device. However, this practice results in (1) high serialization/deserialization (S/D) cost and (2) high memory pressure when off-heap objects are moved back for processing. In this article, we propose TeraHeap , a system that eliminates S/D overhead and expensive GC scans for a large portion of objects in analytics frameworks. TeraHeap relies on three concepts: (1) It eliminates S/D by extending the managed runtime (JVM) to use a second high-capacity heap (H2) over a fast storage device. (2) It offers a simple hint-based interface, allowing analytics frameworks to leverage object knowledge to populate H2. (3) It reduces GC cost by fencing the collector from scanning H2 objects while maintaining the illusion of a single managed heap, ensuring memory safety. We implement TeraHeap in OpenJDK8 and OpenJDK17 and evaluate it with fifteen widely used applications in two real-world big data frameworks, Spark and Giraph. We find that for the same DRAM size, TeraHeap improves performance by up to 73% and 28% compared to native Spark and Giraph. Also, it can still provide better performance by consuming up to \(4.6\times\) and \(1.2\times\) less DRAM than native Spark and Giraph, respectively. TeraHeap can also be used for in-memory frameworks and applying it to the Neo4j Graph Data Science library improves its performance by up to 26%. Finally, it outperforms Panthera, a state-of-the-art garbage collector for hybrid DRAM-NVM memories, by up to 69%.

Talent scouting and standardizing fitness data in football club: systematic review

Talent scouting and fitness data standardization in professional football clubs have been the focus of research in recent years. The role of technology, big data, and data analytics is crucial in reshaping sports performance and bolstering the competitiveness of professional football teams. This review aims to consolidate current research on these technological advancements, examining how they can be effectively harnessed to revolutionize talent sourcing and elevate the competitive standards within football clubs. The review will focus on participants, including professional football players, and intervention interventions such as the implementation of digital technologies, data mining, and machine learning techniques. The study designs will include experimental, observational, and mixed-method studies conducted in football club settings. The analysis highlights the transformative potential of integrating quantitative player statistics with advanced data science and data-driven approaches in revolutionizing sports performance, enabling clubs to make informed recruitment decisions and enhance team performance. In addition, the review focuses on the impact of data analytics on transforming sports performance. The research has demonstrated that these models, specifically classification and regression models, can forecast a football player's performance score with up to 94% accuracy for forward positions.

Fundamentals and Applications Related to Data Science, Machine Learning, and Statistical Processing

Fundamentals and Applications Related to Data Science, Machine Learning, and Statistical Processing

Data protection legislation in Africa and pathways for enhancing compliance in big data health research

BackgroundThe increasing availability of large volumes of personal data from diverse sources such as electronic health records, research programmes, commercial genetic testing, national health surveys and wearable devices presents significant opportunities for advancing public health, disease surveillance, personalized medicine and scientific research and innovation. However, this potential is hampered by a lack of clarity related to the processing and sharing of personal health data, particularly across varying national regulatory frameworks. This often leaves researcher stakeholders uncertain about how to navigate issues around secondary data use, repurposing data for different research objectives and cross-border data sharing.MethodWe analysed 37 data protection legislation across Africa to identify key principles and requirements for processing and sharing of personal health and genetic data in scientific research. On the basis of this analysis, we propose strategies that data science research initiatives in Africa can implement to ensure compliance with data protection laws while effectively reusing and sharing personal data for health research and scientific innovation.ResultsIn many African countries, health and genetic data are categorized as sensitive and subject to stricter protection. Key principles guiding the processing of personal data include confidentiality, non-discrimination, transparency, storage limitation, legitimacy, purpose specification, integrity, fairness, non-excessiveness, accountability and data minimality. The rights of data subjects include the right to be informed, the right of access, the right to rectification, the right to erasure/deletion of data, the right to restrict processing, the right to data portability and the right to seek compensation. Consent and adequacy assessments were the most common legal grounds for cross-border data transfers. However, considerable variation exists in legal requirements for data transfer across countries, potentially creating barriers to collaborative health research across Africa.ConclusionsWe propose several strategies that data science research initiatives can adopt to align with data protection laws. These include developing a standardized module for safe data flows, using trusted data environments to minimize cross-border transfers, implementing dynamic consent mechanisms to comply with consent specificity and data subject rights and establishing codes of conduct to govern the secondary use of personal data for health research and innovation.

Physical climate change exposure and firms' adaptation strategy

AbstractResearch SummaryThis article examines whether and how firms adapt to physical exposures to climate change. I build a novel dataset that compiles information on the adaptation strategies of publicly traded companies around the globe and merge it with climate science data. I find that firms are sensitive to the nature and level of forecasted climate change exposures, and that they adapt more often and more completely to those most salient to their business. Increased physical climate exposure heightens the perceived impact of climate change, leading to a higher degree of adaptation. Furthermore, the positive relationship between firms' climate change exposure and their adaptation is stronger for firms with greater environmental, social, and corporate governance capabilities and those with longer time horizons.Managerial SummaryCompanies are increasingly exposed to the physical impacts of climate change, yet little is known about how they adapt to these long‐term, systemic, and uncertain changes. This study investigates corporate adaptation strategies in response to climate change. By analyzing climate science data and climate change disclosure information from publicly traded companies worldwide, I find that most firms do not adapt to different physical climate change exposures. They adapt more often and more completely when facing higher forecasted climate exposures. Furthermore, firms' environmental, social, and corporate governance capabilities and their time horizons influence their adaptation to greater climate exposures. These findings suggest that targeted interventions may be necessary to improve corporate adaptation to climate change.

Can AI Get a Degree in Geoscience? Performance Analysis of a GPT-Based Artificial Intelligence System Trained for Earth Science (GeologyOracle)

Generative artificial intelligence systems based on the GPT model have shown groundbreaking capabilities in producing scientific texts, revolutionising how geoscientists research and teach. However, there is a noticeable absence of generative AI systems tailored specifically for geoscience, and the efficacy of GPT technology has not been examined within the Earth Science realm. To fill these gaps, we propose a new artificial intelligence system (GeologyOracle) built upon the GPT-4o model and trained on Earth Science data. It is designed to simulate a conversation with a geoscientist, having the capabilities to analyse geologic datasets, suggest new geoscience hypotheses, explain Earth-Science concepts, and interpret geosites. To evaluate the performance of GeologyOracle, the system was tested with 152 geoscience questions provided and evaluated by a panel of geoscience academics on a scale of 0–10. Performance analysis revealed that 79.6% of the answers scored equal to or above the passing mark of 5, with a tendency to deliver high-quality responses (mean: 6.5; median = 7; interquartile range: 5–8). The results demonstrate that GeologyOracle is effective in performing complex geoscience tasks, such as identifying rocks, fossils, and minerals, and interpreting outcrop, core data, and quantitative datasets. The new AI system has exhibited noteworthy ability in the interpretation of internationally-acknowledged geosites situated within geoparks and nature reserves. The performance of the AI system is comparable to that of trained geoscience specialists, suggesting its potential as an assistant in various geoscience fields, including structural geology, palaeontology, geomorphology, sedimentology, and economic geology. While AI does not render geoscientists obsolete, it offers significant potential for accelerating scientific discovery, automating geoscience research, and assisting educators, students, and geotourists.

PACMHCI V8, CHI PLAY, October 2024 Editorial

We are excited to present PACM HCI's 2024 issue on games and play research, which contains 63 original and highly relevant articles covering the entire spectrum of HCI games research. As in the previous year, we used three recommendations ' 'Accept with Minor Revisions', 'Revise and Resubmit', and 'Reject.' For papers that were accepted with minor revisions, the second round of reviews was a 'light-touch' process in which the editorial board members checked the revisions, whereas papers that received Revise and Resubmit received another full round of external reviews with the same reviewers in most cases, and were also subjected to a final selection process. This second revision was treated as a real resubmission, which meant that it was given full consideration, but no guarantee or preferential treatment towards acceptance; a share of the revised papers was ultimately rejected. We would like to acknowledge the efforts that our community has made in adapting to this new process, working together with the submitting authors to achieve high-quality scholarship. The track editorial board consisted of 32 members and a total of 230 external reviewers from around the world ensured a high-quality review process. After the first round of submissions, each paper was handled by a primary track editorial board member who received reviews from a second track editorial board member and two external reviewers so that each submission received at least three high-quality reviews. After reviews were completed and checked for quality, the primary initiated discussion amongst the reviewers and came up with a preliminary recommendation (accept, between accept and revise and resubmit, revise and resubmit, between revise and resubmit and reject, reject). Papers that were in the middle three categories were then discussed in two synchronous virtual track editorial board meetings that took place over two consecutive days. The inclusion of the board meeting at this stage was a new addition to the review process last year. We included it to better calibrate decision making across the committee at this critical point in the review process, ensure consistency in outcomes, promote reflection and consideration at this stage in the process, and mentor newer editorial board members in the review process. We strove for a diverse program approaching games research from a variety of perspectives, including design, engineering, psychology, computer and data science while at the same time only accepting high-quality pieces of work. In this issue, we observe the following distribution of primary contributions: 42.9% of papers self-classify as using qualitative methods, 11.1% use quantitative methods, and 20.6% use mixed methods. Additionally, 3.2% of papers present design artifacts and 6.3% present technical artifacts. Finally, 4.8% of papers employ meta-research methods, 6.3% of papers present a new methodological approach, and 4.8% of papers contribute to the development and validation of theory. All articles in this issue were invited to present at the ACM CHI PLAY 2024 conference. We thank our dedicated team of track editorial board members, external reviewers, and paper authors, who continue to support the new review process and timeline, contributing to the maturation and growth of the PACM HCI games and play research community, and resulting in this issue of 63 exciting and highly relevant articles. This issue's 63 papers reflect the importance of play in our everyday lives, comment on recent trends and technical developments relevant to games and play, and also represent a significant effort of our community in coming together to produce a collection of research that highlights the multifaceted value of play.