False Positive Probability Research Articles

An Efficient Association Rule Mining Algorithm Based on Animal Migration Optimization Processing of Unknown Incidents in Crime Analysis Brance

A new protection scheme was proposed to avoid this problem. It is intended that each node uses a salted and a not salted HLL. If their estimates differ considerably, an attacker attempts to manipulate the estimates of HLL. In addition to avoiding manipulation, the proposed salted and unsalted (SNS) regime can also detect attempts at manipulation. A practical configuration showing how manipulation attempts can be detected in a low false positive probability has been shown to be applicable to this SNS scheme. Therefore, if merge ability is to be preserved it can be an interesting approach to protect HLLs from avoidance. In this paper the proposal for a new mining algorithm based on Animal Migration Optimization is made to decrease the number of Association Rules called ARM-AMO. The idea is to remove from the data rules which are not highly supportive and unnecessary. First of all, common item sets and association rules are generated with an Apriori algorithm. AMO also reduces the number of association rules incorporated in a new fitness function. In here, we provide a well-organized mechanism for incident derivation under the unwanted incident. This mechanism very useful for measure the heavy load of an incoming incident and exact calculation of the probability. In additional method is a Select-ability mechanism, which performs an important responsibility in incident derivation under the unwanted incident in both the settled and the unknown incident. A model for signifying derivative incident introduced jointly with an Advanced Sampling Technique that come close to the derived incident probabilities. This augmentation executed the prioritization techniques. In this prioritization techniques, recognize such cases in which the order of incident finding is strong-minded and mechanism for the definition of a settled detection execution.

Energy-Efficient Superconductor Bloom Filters for Streaming Data Inspection

Bloom filters can be used in network intrusion detection systems to detect known attack signatures in packet payloads. In this paper we propose and analyze the potential application of superconductor flux quantum technology for streaming data inspection with Bloom filters designed with Reciprocal Quantum Logic (RQL). This paper describes the gate-level design, performance, and energy-efficiency analysis of three superconductor 2 Kbit Bloom filters with 1) the run-time selection of the number of hashes per stream, and 2) different numbers of input streams per Bloom filter. The Bloom filter circuits were designed using a bottom-up approach with manual placing and routing of basic RQL gates. The design complexity is below 97K Josephson junctions. The highest clock frequency reached in the simulation of the circuits is 14.7 GHz. The false positive ra tes of the RQL Bloom filters are in very close agreement with the theoretical expectations of the false positive probability for the filters. For the cryocooling efficiency of 0.1 percent, the RQL Bloom filters demonstrate high energy efficiency in the range of ∼1.5-43.6 pJ/stream/operation at room temperature for stream lengths from 16 to 256 bits. All circuits are designed and simulated for the 248 nm MIT Lincoln Laboratory SFQ5ee fabrication process.

A Catalog of Short Period Spectroscopic and Eclipsing Binaries Identified from the LAMOST and PTF Surveys

Binaries play key roles in determining stellar parameters and exploring stellar evolution models. We build a catalog of 88 eclipsing binaries with spectroscopic information, taking advantage of observations from both the Large Sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) and the Palomar Transient Factory (PTF) surveys. A software pipeline is constructed to identify binary candidates by examining their light curves. The orbital periods of binaries are derived from the Lomb-Scargle method. The key distinguishing features of eclipsing binaries are recognized by a new filter \textit{Flat Test}. We classify the eclipsing binaries by applying Fourier analysis on the light curves. Among all the binary stars, 13 binaries are identified as eclipsing binaries for the first time. The catalog contains information: position, primary eclipsing magnitude and time, eclipsing depth, the number of photometry and radial velocity observations, largest radial velocity difference, binary type, the effective temperature of observable star $T_{\rm eff}$, and surface gravity of observable star log \emph{g}. The false-positive probability is calculated by using both a Monte Carlo simulation and real data from the SDSS Stripe 82 Standard Catalog. The binaries in the catalog are mostly with a period of less than one day. The period distribution shows a 0.22-day cut-off which is consistent with the low probability of an eclipsing binary rotating with such a period.

CTLA-4 rs231775 and risk of acute renal graft rejection: an updated meta-analysis with trial sequential analysis

Contrasting results exist on the association between CTLA-4 rs231775 and acute rejection in kidney transplant recipients. We herein conducted an updated systematic review with meta-analysis and trial sequential analysis (TSA) to clarify this relationship and to establish whether the current evidence is sufficient to draw firm conclusions. In addition, noteworthiness of significant pooled odds ratios (ORs) was estimated by false positive report probability (FPRP). A comprehensive search was performed through PubMed, Web of Knowledge, Cochrane Library and Open Grey up to October 2019. Fifteen independent cohorts, including a total of 5,401 kidney transplant recipients, were identified through the systematic review. Overall, no association was detected with the allelic (OR 1.07, 95% CI 0.88–1.30, P = 0.49), dominant (OR 0.94, 95% CI 0.73–1.22, P = 0.66) or the recessive (OR 1.18, 95% CI 0.97–1.43, P = 0.096) model of CTLA-4 rs231775. In each genetic model, the cumulative Z-curve in TSA crossed the futility boundary and entered the futility area. In addition, none of the significant genetic comparisons detected in the subsequent and sensitivity analyses or in previously reported meta-analyses were found to be noteworthy by FPRP. In conclusion, this study provides strong evidence that CTLA-4 rs231775 is not a clinically-relevant genetic risk determinant of acute rejection after renal transplantation.

YTHDC1 gene polymorphisms and hepatoblastoma susceptibility in Chinese children: A seven-center case-control study.

Hepatoblastoma is a commonly occurring embryonal tumors in children. N6-methyladenosine (m6 A) plays a critical role in gene expression, thus contributing to the occurrence and progression of cancer. RNA splicing is regulated by the nuclear m6 A reader YTHDC1, yet the roles of YTHDC1 polymorphisms in hepatoblastoma remain unclear. We conducted a seven-center case-control study to determine the association between YTHDC1 gene polymorphisms (rs2293596 T>C, rs2293595 T>C and rs3813832 T>C) and hepatoblastoma susceptibility. We recruited 313 hepatoblastoma patients and 1446 healthy controls. There was no significant association between all of these polymorphisms and hepatoblastoma susceptibility in single locus or combined analysis. Stratification analysis revealed that rs2293596 TC/CC genotype carriers had a higher risk of developing hepatoblastoma in the subgroup of clinical stages III + IV [adjusted odds ratio (OR) = 1.80, 95% confidence interval (CI) = 1.18-2.76, p = 0.007]. In addition, 3 risk genotype carriers are more likely to develop hepatoblastoma in the subgroup of clinical stages III + IV (adjusted OR = 1.80, 95% CI = 1.18-2.76, p = 0.007). Furthermore, false-positive probability analysis was used to notarize our findings. Haplotype analysis indicated that there was no significant association between inferred haplotypes of YTHDC1 gene based on observed genotypes and hepatoblastoma risk. In conclusion, our findings suggest that the rs2293596 T>C polymorphism may contribute to hepatoblastoma susceptibly and YTHDC1 gene polymorphisms may have a cumulative effect on hepatoblastoma risk.

A comprehensive evaluation of single nucleotide polymorphisms associated with atrophic gastritis risk: A protocol for systematic review and network meta-analysis.

Single nucleotide polymorphisms (SNPs) have been inconsistently associated with atrophic gastritis (AG) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with AG. To identify all associated studies of SNPs and AG published, databases had been searched through January 2020 from the databases of PubMed, China National Knowledge Infrastructure (CNKI), Web of Science, Embase, the Chinese Science and Technology Periodical Database (VIP), Cochrane Library, and Wanfang databases. With the help of network meta-analysis and Thakkinstian algorithm, the best genetic model with the strongest correlation with AG was selected, the final result - matching to the noteworthy correlation - was obtained by referring to the false positive reporting rate (false positive report probability, FPRP). Based on STREGA's stated criteria, the methodological quality of the data we collected was valued. Both Stata 14.0 and GeMTC will be used for a comprehensive review of the system and will be used in our meta-analysis. This study will provide a high-quality evidence to find the SNP most associated with AG susceptibility and the best genetic model. This study will explore which SNP is most associated with AG susceptibility. INPLASY202050016.

A comprehensive evaluation of association between homocysteine levels and single nucleotide polymorphisms with hypertension risk: A protocol of systematic review and network meta-analysis.

According to the relevant reports that single nucleotide polymorphisms (SNPs) may contribute to change of homocysteine (HCY) levels and increase the risk of hypertension (HTN). During the inconsistent results, this meta-analysis purpose is systematically review and synthesized relevant data on HCY levels and SNPs in HTN. The systematic search database, from the following database to find out the association studies of SNPs and HTN publications up until March 2020 from the databases of PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), the Chinese Science and Technology Periodical Database (VIP) and Wan fang databases, and Chinese Biomedical Literature Database (CBM). Network meta-analysis and Thakkinstian's algorithm were used to select the most appropriate genetic model, along with false positive report probability (FPRP) for noteworthy associations. All statistical analyses were calculated with STATA software (version 14.0; StataCorp, College Station, TX). This meta-analysis will provide high-quality evidence to the effects of SNP on HTN and levels of HCY, and find between SNPs and HTN susceptibility on in all the genetic models, and choose the best one. This meta-analysis will research which SNP is the most correlated with HTN risk. INPLASY202050002.

A comprehensive evaluation of single nucleotide polymorphisms associated with osteosarcoma risk: A protocol for systematic review and network meta-analysis.

Single nucleotide polymorphisms (SNPs) have been inconsistently associated with osteosarcoma (OS) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with OS. Databases were searched to identify association studies of SNPs and OS published through January 2020 from the databases of PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, the Chinese Science and Technology Periodical Database, and Wan fang databases. Network meta-analysis and Thakkinstian algorithm were used to select the most appropriate genetic model, along with false positive report probability for noteworthy associations. The methodological quality of data was assessed based on the STrengthening the REporting of Genetic Association Studies statement Stata 14.0 will be used for systematic review and meta-analysis. This study will provide a high-quality evidence to find the SNP most associated with OS susceptibility and the best genetic model. This study will explore which SNP is most associated with OS susceptibility. INPLASY202040023.

A comprehensive evaluation of single nucleotide polymorphisms associated with gastric cancer risk: A protocol for systematic review and network meta-analysis.

Single nucleotide polymorphisms (SNPs) have been inconsistently associated with gastric cancer (GC) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with GC. Databases were searched to identify association studies of SNPs and GC published through January 2020 from the databases of PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, the Chinese Science and Technology Periodical Database, and Wan fang databases. Network meta-analysis and Thakkinstian algorithm were used to select the most appropriate genetic model, along with false positive report probability for noteworthy associations. The methodological quality of data was assessed based on the STrengthening the REporting of Genetic Association Studies statement Stata 14.0 will be used for systematic review and meta-analysis. This study will provide a high-quality evidence to find the SNP most associated with GC susceptibility and the best genetic model. This study will explore which SNP is most associated with GC susceptibility. INPLASY202040132.

Patient-based quality control for glucometers: using the moving sum of positive patient results and moving average.

IntroductionThe capability of glucometer internal quality control (QC) in detecting varying magnitude of systematic error (bias), and the potential use of moving sum of positive results (MovSum) and moving average (MA) techniques as potential alternatives were evaluated.Materials and methodsThe probability of error detection using routine QC and manufacturer’s control limits were investigated using historical data. Moving sum of positive results and MA algorithms were developed and optimized before being evaluated through numerical simulation for false positive rate and probability of error detection.ResultsWhen the manufacturer’s default control limits (that are multiple times higher than the running standard deviation (SD) of the glucometer) was used, they had 0-75% probability of detecting small errors up to 0.8 mmol/L. However, the error detection capability improved to 20-100% when the running SD of the glucometer was used. At a binarization threshold of 6.2 mmol/L and block sizes of 200 to 400, MovSum has a 100% probability of detecting a bias that is greater than 0.5 mmol/L. Compared to MovSum, the MA technique had lower probability of bias detection, especially for smaller bias magnitudes; MA also had higher false positive rates.ConclusionsThe MovSum technique is suited for detecting small, but clinically significant biases. Point of care QC should follow conventional practice by setting the control limits according to the running mean and SD to allow proper error detection. The glucometer manufacturers have an active role to play in liberalizing QC settings and also enhancing the middleware to facility patient-based QC practices.

A comprehensive assessment of single nucleotide polymorphisms associated with pancreatic cancer risk: A protocol for systematic review and network meta-analysis.

Single nucleotide polymorphisms (SNPs) have been inconsistently associated with pancreatic cancer (PC) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with PC. Databases were searched to identify association studies of SNPs and PC published through January 2020 from the databases of PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, the Chinese Science and Technology Periodical Database (VIP) and Wanfang databases. Network meta-analysis and Thakkinstian algorithm were used to select the most appropriate genetic model, along with false positive report probability (FPRP) for noteworthy associations. The methodological quality of data was assessed based on the STREGA statement Stata 14.0 will be used for systematic review and meta-analysis. This study will provide a high-quality evidence to find the SNP most associated with pancreatic cancer susceptibility and the best genetic model. This study will explore which SNP is most associated with pancreatic cancer susceptibility.Registration: INPLASY202040023.

Transit least-squares survey

The Sun-like star Kepler-160 (KOI-456) has been known to host two transiting planets, Kepler-160 b and c, of which planet c shows substantial transit-timing variations (TTVs). We studied the transit photometry and the TTVs of this system in our search for a suspected third planet. We used the archival Kepler photometry of Kepler-160 to search for additional transiting planets using a combination of our Wōtan detrending algorithm and our transit least-squares detection algorithm. We also used the Mercury N-body gravity code to study the orbital dynamics of the system in trying to explain the observed TTVs of planet c. First, we recovered the known transit series of planets Kepler-160 b and c. Then we found a new transiting candidate with a radius of 1.91−0.14+0.17 Earth radii (R⊕), an orbital period of 378.417−0.025+0.028 d, and Earth-like insolation. The vespa software predicts that this signal has an astrophysical false-positive probability of FPP3 = 1.8 × 10−3 when the multiplicity of the system is taken into account. Kepler vetting diagnostics yield a multiple event statistic of MES = 10.7, which corresponds to an ~85% reliability against false alarms due to instrumental artifacts such as rolling bands. We are also able to explain the observed TTVs of planet c with the presence of a previously unknown planet. The period and mass of this new planet, however, do not match the period and mass of the new transit candidate. Our Markov chain Monte Carlo simulations of the TTVs of Kepler-160 c can be conclusively explained by a new nontransiting planet with a mass between about 1 and 100 Earth masses and an orbital period between about 7 and 50 d. We conclude that Kepler-160 has at least three planets, one of which is the nontransiting planet Kepler-160 d. The expected stellar radial velocity amplitude caused by this new planet ranges between about 1 and 20 m s−1. We also find the super-Earth-sized transiting planet candidate KOI-456.04 in the habitable zone of this system, which could be the fourth planet.

EDNA‐based monitoring: Advancement in management and conservation of critically endangered killifish species

AbstractEcosystems are currently changing at unprecedented rates due to anthropogenic influences. Application of appropriate management regimes and mitigation measures requires knowledge of ecological community composition and monitoring of any changes that occur. Environmental DNA‐based monitoring is becoming increasingly common and offers substantial potential as a noninvasive method associated with highly repeatable and reliable results. In this study, we monitored river systems in Western Greece that have been strongly impacted by anthropogenic activities and the spread of an alien invasive fish species, the Eastern mosquitofish (Gambusia holbrooki). This invasive species has been credited as the major cause for the drastic decline of two endemic killifish species (Valencia letourneuxi and Valencia robertae). Here, we investigated the efficacy of an environmental DNA (eDNA‐based) method of detection for all three species, as an alternative to conventional monitoring methods. Initially, a mesocosm experiment provided material for the design and validation of the sampling protocol. This was followed by two sampling periods in the field conducted in autumn 2017 and 2018, comparing the novel eDNA assays with the conventional surveying methods in six and 20 systems, respectively. eDNA detection consistently outperformed the traditional monitoring methods for both V. letourneuxi and V. robertae and was comparable for the invasive G. holbrooki. This supports the now increasing body of literature, highlighting the benefits of species‐specific, targeted eDNA assays for the assessment of threatened and/or invasive species, one which can be utilized by conservation organizations and government bodies alike. However, we note that care should always be taken when designing such tools and strict validation steps should be adhered to, particularly with respect to minimizing the probability of false positives and negatives.

Plateau de Bure High-z Blue Sequence Survey 2 (PHIBSS2): Search for Secondary Sources, CO Luminosity Functions in the Field, and the Evolution of Molecular Gas Density through Cosmic Time*

Abstract We report on the results of a search for serendipitous sources in CO emission in 110 cubes targeting CO(2 − 1), CO(3 − 2), and CO(6 − 5) at z ∼ 1–2 from the second Plateau de Bure High-z Blue Sequence Survey (PHIBSS2). The PHIBSS2 observations were part of a 4 yr legacy program at the IRAM Plateau de Bure Interferometer aimed at studying early galaxy evolution from the perspective of molecular gas reservoirs. We present a catalog of 67 candidate secondary sources from this search, with 45 of the 110 data cubes showing sources in addition to the primary target that appear to be field detections, unrelated to the central sources. This catalog includes redshifts, line widths, and fluxes, as well as an estimation of their reliability based on their false-positive probability. We perform a search in the 3D Hubble Space Telescope/CANDELS catalogs for the secondary CO detections and tentatively find that ∼64% of these have optical counterparts, which we use to constrain their redshifts. Finally, we use our catalog of candidate CO detections to derive the CO(2 − 1), CO(3 − 2), CO(4 − 3), CO(5 − 4), and CO(6 − 5) luminosity functions over a range of redshifts, as well as the molecular gas mass density evolution. Despite the different methodology, these results are in very good agreement with previous observational constraints derived from blind searches in deep fields. They provide an example of the type of “deep-field” science that can be carried out with targeted observations.

Midas: Microcluster-Based Detector of Anomalies in Edge Streams

Given a stream of graph edges from a dynamic graph, how can we assign anomaly scores to edges in an online manner, for the purpose of detecting unusual behavior, using constant time and memory? Existing approaches aim to detect individually surprising edges. In this work, we propose Midas, which focuses on detecting microcluster anomalies, or suddenly arriving groups of suspiciously similar edges, such as lockstep behavior, including denial of service attacks in network traffic data. Midas has the following properties: (a) it detects microcluster anomalies while providing theoretical guarantees about its false positive probability; (b) it is online, thus processing each edge in constant time and constant memory, and also processes the data 108–505 times faster than state-of-the-art approaches; (c) it provides 46%-52% higher accuracy (in terms of AUC) than state-of-the-art approaches.

Frequentist Properties of Bayesian Multiplicity Control for Multiple Testing of Normal Means

We consider the standard problem of multiple testing of normal means, obtaining Bayesian multiplicity control by assuming that the prior inclusion probability (the assumed equal prior probability that each mean is nonzero) is unknown and assigned a prior distribution. The asymptotic frequentist behavior of the Bayesian procedure is studied, as the number of tests grows. Studied quantities include the false positive probability, which is shown to go to zero asymptotically. The asymptotics of a Bayesian decision-theoretic approach are also presented.

Accounting for Multiple Comparisons in Statistical Analysis of the Extensive Bioassay Data on Glyphosate.

Glyphosate is a widely used herbicide worldwide. In 2015, the International Agency for Research on Cancer (IARC) reviewed glyphosate cancer bioassays and human studies and declared that the evidence for carcinogenicity of glyphosate is sufficient in experimental animals. We analyzed 10 glyphosate rodent bioassays, including those in which IARC found evidence of carcinogenicity, using a multiresponse permutation procedure that adjusts for the large number of tumors eligible for statistical testing and provides valid false-positive probabilities. The test statistics for these permutation tests are functions of p values from a standard test for dose-response trend applied to each specific type of tumor. We evaluated 3 permutation tests, using as test statistics the smallest p value from a standard statistical test for dose-response trend and the number of such tests for which the p value is less than or equal to .05 or .01. The false-positive probabilities obtained from 2 implementations of these 3 permutation tests are: smallest p value: .26, .17; p values ≤ .05: .08, .12; and p values ≤ .01: .06, .08. In addition, we found more evidence for negative dose-response trends than positive. Thus, we found no strong evidence that glyphosate is an animal carcinogen. The main cause for the discrepancy between IARC's finding and ours appears to be that IARC did not account for the large number of tumor responses analyzed and the increased likelihood that several of these would show statistical significance simply by chance. This work provides a more comprehensive analysis of the animal carcinogenicity data for this important herbicide than previously available.

Genetic variants in migraine: a field synopsis and systematic re-analysis of meta-analyses

ObjectiveNumerous genetic variants from meta-analyses of observational studies and GWAS were reported to be associated with migraine susceptibility. However, due to the random errors in meta-analyses, the noteworthiness of the results showing statistically significant remains doubtful. Thus, we performed this field synopsis and re-analysis study to evaluate the noteworthiness using a Bayesian approach in hope of finding true associations.MethodsRelevant meta-analyses from observational studies and GWAS examining correlation between all genetic variants and migraine risk were included in our study by a PubMed search. Identification of noteworthy associations were analyzed by false-positive rate probability (FPRP) and Bayesian false discovery probability (BFDP). Using noteworthy variants, GO enrichment analysis were conducted through DAVID online tool. Then, the PPI network and hub genes were performed using STRING database and CytoHubba software.ResultsAs for 8 significant genetic variants from observational studies, none of which showed noteworthy at prior probability of 0.001. Out of 47 significant genetic variants in GWAS, 36 were noteworthy at prior probability of 0.000001 via FPRP or BFDP. We further found the pathways “positive regulation of cytosolic calcium ion concentration” and “inositol phosphate-mediated signaling” and hub genes including MEF2D, TSPAN2, PHACTR1, TRPM8 and PRDM16 related to migraine susceptibility.ConclusionHerein, we have identified several noteworthy variants for migraine susceptibility in this field synopsis. We hope these data would help identify novel genetic biomarkers and potential therapeutic target for migraine.

Distributed SCFMBF Based Protocol for Integrity In Cloud Storage System (DPICS)

Cloud storage allowed the data owners to store their data without the burden of local hardware. There were some security concerns because of the cloud being untrusted. To make sure the stored data was intact since it was impractical to download the full data, a security mechanism named integrity check was used. Integrity check was achieved by probabilistic structures such as bloom filter and cuckoo filter. Uploading data file on to one cloud server could be a point of failure, instead the file could be distributed over l servers. Distributed SCFMBF Based Protocol for Integrity in Cloud Storage System (DPICS) was proposed to remotely check data integrity in a more effective way. Smart Cuckoo Filter Modified by Bloom Filter (SCFMBF) was a protocol that improved some of the performance properties of cuckoo filter such as false positive rate and insertion performance and solved some drawbacks of the cuckoo algorithm such as endless loop. Main characteristic of the bloom filter was used to improve cuckoo filter as the protocol name describes. First bloom filter was used as the integrity check method in cloud but bloom filter was not suitable for dynamic environment, SCFMBF was substituted for bloom filter because it had low false positive probability in integrity check and could cope well with dynamic data. How DPICS was more efficient than other previous works, was shown in terms of false positive probability, integrity check and retrievability.

Accuracy of panoramic radiography for degenerative changes of the temporomandibular joint

Background:Temporomandibular joint (TMJ) morphologies are complex, and changes in joint components have been studied extensively. TMJ conditions have many different etiologies, appearances, and relevant clinical significance.Objective:The objective of this study was to evaluate the concordance of the diagnosis of degenerative changes in the TMJ in panoramic radiographs.Materials and Methods:Cone beam computed tomography (CBCT) was used as a reference standard. Images of 84 patients (168 TMJs), 61 females (72.6%) and 23 males (27.4%) with an average age of 47.4 years, were evaluated by three radiologists who established the presence or absence of degenerative changes in the jaw heads. The data were collected and organized in a spreadsheet. Concordance between evaluators was analyzed using agreement percentages, statistical κ, and confidence intervals. In the analysis of compliance with CBCT, sensitivity, specificity, predictive positive and negative values, and probabilities of false positives and negatives were also calculated. All inferential tests were performed with a 5% significance level.Results:The percentage of agreement among raters in panoramic radiographs ranged from 66.7% to 82.9%, considered mild to moderate. Correlation between radiographic and tomographic images ranged from 45.5% to 64.9% in the inter-evaluator reviews, representing a very mild agreement. Sensitivity ranged from 28.6% to 58.7% and specificity from 66.7% to 100.0%. Positive predictive value ranged from 77.1% to 100.0%; the negative predictive value was lower, ranging from 32.2% to 54.8%. The probability of false negatives was higher than that of false positives, ranging from 45.2% to 67.8%.Conclusion:The rater did not reach acceptable diagnosis levels.