{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":56,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":56,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"5d65661dfa04","filters":{"venue":"Open Journal of Statistics"}},"results":[{"id":"W1968980970","doi":"10.4236/ojs.2013.32017","title":"The Statistical Analysis of Interval-Censored Failure Time Data with Applications","year":2013,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":38,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph; University of Waterloo","funders":"","keywords":"Censoring (clinical trials); Nonparametric statistics; Parametric statistics; Statistics; Interval (graph theory); Computer science; Accelerated failure time model; Parametric model; Survival analysis; Mathematics; Data mining","authors":[{"name":"Radhey S. Singh","is_ca":true},{"name":"Dishna P. Totawattage","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09487944757262302,"gpt":0.4011815509821152,"spread":0.3063021034094922,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02050177,0.0009133192,0.001842304,0.003611602,0.000540828,0.00152585,0.002305894,0.001267559,0.002326733],"category_scores_gemma":[0.09224784,0.0004801947,0.001646249,0.004925691,0.00218529,0.001902057,0.001765707,0.003119731,0.0005594368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006121297,"about_ca_system_score_gemma":0.001257493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008691612,"about_ca_topic_score_gemma":0.0004857785,"domain_scores_codex":[0.9827163,0.01247313,0.0006825808,0.00099324,0.002920782,0.0002139315],"domain_scores_gemma":[0.8952894,0.09094521,0.004064285,0.006776633,0.002557741,0.0003667652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00041583,0.0003311636,0.01868317,0.002245478,0.001458158,0.0008988311,0.0009800971,0.2577825,0.006799541,0.3211932,0.005450166,0.383762],"study_design_scores_gemma":[0.00003683508,0.0004745262,0.00804729,0.0003071228,0.0001317037,0.0006837643,0.0002383157,0.7542048,0.002616703,0.2234913,0.009671401,0.00009624903],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005260954,0.001015552,0.9927506,0.0001305384,0.00005163206,0.00005394197,0.000150515,0.000174503,0.0004116634],"genre_scores_gemma":[0.2129501,0.00411313,0.7792666,0.000188701,0.0003318919,0.0008740342,0.0009462108,0.0001961369,0.001133136],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02050177,"threshold_uncertainty_score":0.108425,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2008984269","doi":"10.4236/ojs.2014.45033","title":"Distribution of the Sample Correlation Matrix and Applications","year":2014,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":38,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Moncton","funders":"","keywords":"Mathematics; Null (SQL); Correlation; Sample (material); Statistics; Null distribution; Multivariate normal distribution; Matrix (chemical analysis); Population; Multivariate statistics; Applied mathematics; Statistical physics; Statistical hypothesis testing; Computer science; Physics; Test statistic; Thermodynamics; Geometry; Materials science","authors":[{"name":"T. Pham‐Gia","is_ca":true},{"name":"Vartan Choulakian","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04152441248663195,"gpt":0.3676950678739614,"spread":0.3261706553873295,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004825637,0.001032024,0.0009063455,0.002631847,0.00063481,0.002018499,0.001140819,0.001757283,0.007724409],"category_scores_gemma":[0.04228957,0.0005278086,0.0007742801,0.002936114,0.002477081,0.002095762,0.002216011,0.002379253,0.001570288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001238169,"about_ca_system_score_gemma":0.001253157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00158128,"about_ca_topic_score_gemma":0.001051308,"domain_scores_codex":[0.9973207,0.001425057,0.0001174594,0.0003497262,0.0006615614,0.0001255524],"domain_scores_gemma":[0.982316,0.01303443,0.0009299745,0.00148016,0.001960411,0.0002789921],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004482158,0.00005169945,0.001275762,0.0002356697,0.00003006881,0.0005168321,0.000267034,0.08120652,0.002208479,0.8675959,0.005524131,0.04104307],"study_design_scores_gemma":[0.00002131384,0.00005879129,0.001152514,0.0001604092,0.00002357671,0.001008094,0.0001200544,0.3864191,0.001713952,0.5965896,0.01266536,0.00006722396],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008089703,0.002737895,0.9752887,0.0009953137,0.0001280658,0.00005718212,0.0001540411,0.0002689173,0.01228016],"genre_scores_gemma":[0.5856179,0.01476759,0.3760238,0.001045302,0.001443367,0.0007929867,0.0007444571,0.0005886462,0.01897595],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007724409,"threshold_uncertainty_score":0.0258407,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2622376831","doi":"10.4236/ojs.2017.73029","title":"Confidence Intervals for the Mean of Non-Normal Distribution: Transform or Not to Transform","year":2017,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":30,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada","keywords":"Statistics; Confidence interval; Mathematics; Normality; CDF-based nonparametric confidence interval; Confidence distribution; Sample size determination; Coverage probability; Robust confidence intervals; Transformation (genetics); Normal distribution; Parametric statistics; Confidence region; Data transformation; Power transform; Computer science; Data mining","authors":[{"name":"Jolynn Pek","is_ca":true},{"name":"Augustine Wong","is_ca":true},{"name":"Octavia Wong","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.137576029597273,"gpt":0.4576476642110374,"spread":0.3200716346137643,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04226244,0.00112281,0.002095683,0.003803692,0.00101536,0.004104176,0.003564101,0.003779426,0.005599149],"category_scores_gemma":[0.3645871,0.0005589938,0.001847994,0.004063843,0.00538889,0.007222595,0.003362933,0.00717593,0.001143058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001584923,"about_ca_system_score_gemma":0.001796418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001746119,"about_ca_topic_score_gemma":0.0007960466,"domain_scores_codex":[0.9659823,0.01832712,0.002200799,0.00469127,0.007960105,0.0008383027],"domain_scores_gemma":[0.6470501,0.3042013,0.01472209,0.02040333,0.01242351,0.00119968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0008210765,0.0001816162,0.01859994,0.002050208,0.0008457768,0.001043484,0.001863386,0.05067929,0.00218001,0.6456494,0.01644371,0.259642],"study_design_scores_gemma":[0.0001893973,0.000319028,0.008568317,0.001640383,0.0003142811,0.001521991,0.0007329792,0.168455,0.005064637,0.7805625,0.03232918,0.0003022104],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01321313,0.005935332,0.9721129,0.001651677,0.0007387503,0.0001271577,0.0004508501,0.0005586909,0.005211497],"genre_scores_gemma":[0.5277591,0.005571604,0.4581897,0.001803593,0.001124432,0.001163598,0.00162446,0.0006973428,0.002066113],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04226244,"threshold_uncertainty_score":0.2235078,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1953696579","doi":"10.4236/ojs.2015.55044","title":"Confirmatory Factor Analysis of the Youth Experiences Survey for Sport (YES-S)","year":2015,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Youth Development and Social Support","field":"Social Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Brock University","funders":"","keywords":"Confirmatory factor analysis; Exploratory factor analysis; Psychology; Athletes; Scale (ratio); Construct validity; Context (archaeology); Structural equation modeling; Psychometrics; Social psychology; Applied psychology; Developmental psychology; Mathematics; Statistics; Medicine","authors":[{"name":"Philip Sullivan","is_ca":true},{"name":"Kaitlyn LaForge-MacKenzie","is_ca":true},{"name":"Matthew Marini","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2168443356022707,"gpt":0.4066124021299979,"spread":0.1897680665277272,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01691555,0.0007491944,0.0008647945,0.002435373,0.0009875387,0.0008356439,0.0005214571,0.000348176,0.002817185],"category_scores_gemma":[0.03103259,0.0003249265,0.001485099,0.002263085,0.0005588863,0.000440296,0.001096298,0.0009953333,0.0005347815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006309156,"about_ca_system_score_gemma":0.003954757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008347793,"about_ca_topic_score_gemma":0.01374091,"domain_scores_codex":[0.992691,0.003940907,0.0006790988,0.0005443973,0.001864978,0.0002796124],"domain_scores_gemma":[0.9782779,0.008528143,0.001420857,0.001631306,0.009651108,0.000490618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005094892,0.0007264625,0.8597796,0.0004748173,0.0003659944,0.0003002625,0.01178618,0.0009187784,0.001682889,0.002805334,0.005837397,0.1148128],"study_design_scores_gemma":[0.0001631588,0.001220542,0.970984,0.000299041,0.000202827,0.0001921637,0.009729871,0.005887771,0.001519234,0.001839287,0.007910253,0.00005180853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.963056,0.0001586966,0.02490127,0.0004438534,0.00009884265,0.003616778,0.003426137,0.00009132084,0.004207187],"genre_scores_gemma":[0.9602254,0.0001494724,0.02805285,0.0001209904,0.00002899017,0.00539826,0.004594101,0.00004384207,0.001386189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01691555,"threshold_uncertainty_score":0.089459,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1999151257","doi":"10.4236/ojs.2013.32013","title":"Bayesian Estimation for GEV-B-Spline Model","year":2013,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Moncton; Institut National de la Recherche Scientifique","funders":"","keywords":"Markov chain Monte Carlo; Quantile; Bayesian probability; Covariate; Statistics; Bayesian inference; Spline (mechanical); Mathematics; Econometrics; Computer science","authors":[{"name":"Bouchra Nasri","is_ca":true},{"name":"Salah‐Eddine El Adlouni","is_ca":true},{"name":"Taha B. M. J. Ouarda","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01578645831798866,"gpt":0.2837846234308781,"spread":0.2679981651128894,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003832993,0.000421917,0.001092682,0.001094879,0.0004073923,0.0008969252,0.001389799,0.001106142,0.002922424],"category_scores_gemma":[0.0121179,0.000591201,0.000940437,0.00144946,0.0005929235,0.001211295,0.0009996484,0.001821662,0.0006618762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005551785,"about_ca_system_score_gemma":0.001285727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007590699,"about_ca_topic_score_gemma":0.006461634,"domain_scores_codex":[0.9986786,0.0008596675,0.00004365196,0.0001544887,0.0001755199,0.00008798241],"domain_scores_gemma":[0.996196,0.002896351,0.0002491458,0.0002394008,0.0003245751,0.00009454739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001071228,0.0000432737,0.005688004,0.0001746383,0.0001023873,0.0001341835,0.0001179109,0.8416578,0.001408231,0.09361619,0.002221997,0.05472817],"study_design_scores_gemma":[0.000008541318,0.00001044174,0.0007341683,0.00001537037,0.000007643423,0.00003551918,0.000009135843,0.9722002,0.0001161066,0.02614757,0.0007036585,0.00001157883],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01212929,0.0002532711,0.9867746,0.000109854,0.00001288457,0.00001703744,0.0001657596,0.0001782695,0.0003591141],"genre_scores_gemma":[0.5295346,0.001626067,0.4618716,0.0001319891,0.0001385913,0.0002739577,0.002150748,0.0003194897,0.003953061],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007590699,"threshold_uncertainty_score":0.02027106,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1971272938","doi":"10.4236/ojs.2014.46043","title":"Confirmatory Factor and Invariance Analyses of the Motivation to Control Prejudiced Reactions Scale","year":2014,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Social and Intergroup Psychology","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Confirmatory factor analysis; Measurement invariance; Equivalence (formal languages); Scale (ratio); Psychology; Econometrics; Factor analysis; Statistics; Scale invariance; Mathematics; Social psychology; Structural equation modeling; Pure mathematics; Geography; Cartography","authors":[{"name":"Todd G. Morrison","is_ca":true},{"name":"Melanie A. Morrison","is_ca":false},{"name":"Lorraine McDonagh","is_ca":true},{"name":"Daniel Regan","is_ca":false},{"name":"Sarah-Jane McHugh","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.085714206602683,"gpt":0.4093220566005834,"spread":0.3236078499979004,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02057653,0.0007702202,0.0006258627,0.002776657,0.001528273,0.001141783,0.0005389741,0.0003230368,0.003855133],"category_scores_gemma":[0.05408027,0.0003200462,0.002224393,0.00189799,0.00122096,0.0007664272,0.001317435,0.001652094,0.0006172636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001023178,"about_ca_system_score_gemma":0.005622646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01960456,"about_ca_topic_score_gemma":0.02338973,"domain_scores_codex":[0.9923468,0.003336261,0.0006368698,0.0006145602,0.002559721,0.000505751],"domain_scores_gemma":[0.9615552,0.01669117,0.002017141,0.004327729,0.01447807,0.0009305115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006000615,0.001165753,0.7451344,0.0002560991,0.0003696815,0.0003227693,0.01828306,0.002108403,0.009709836,0.01072772,0.003462694,0.2078596],"study_design_scores_gemma":[0.0001224332,0.0007673963,0.9712533,0.0001125349,0.0001618392,0.000158897,0.007633155,0.007780799,0.003220428,0.003980112,0.004746744,0.00006230382],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9563336,0.0001209888,0.03142076,0.0003278536,0.0001033666,0.001969931,0.0009096953,0.0001233427,0.008690364],"genre_scores_gemma":[0.9750875,0.00009713877,0.01991956,0.00005497225,0.00002921863,0.001992754,0.00148318,0.0000628804,0.001272838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02057653,"threshold_uncertainty_score":0.1088203,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2025347578","doi":"10.4236/ojs.2012.23034","title":"Subsampling Method for Robust Estimation of Regression Models","year":2012,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Outlier; Robust regression; Robustness (evolution); Regression analysis; Regression; Mathematics; Computer science; Local regression; Linear regression; Statistics; Polynomial regression","authors":[{"name":"Min Tsao","is_ca":true},{"name":"Ling Xiao","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05906675417687906,"gpt":0.3394301466337274,"spread":0.2803633924568483,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006689254,0.001196834,0.001456235,0.001768872,0.0005375714,0.00100142,0.002079837,0.001552283,0.002702835],"category_scores_gemma":[0.02215834,0.0006891277,0.001824588,0.001266166,0.001179746,0.001466446,0.001288905,0.002199591,0.001055077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007448689,"about_ca_system_score_gemma":0.001070136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003806649,"about_ca_topic_score_gemma":0.00280857,"domain_scores_codex":[0.9954769,0.002623829,0.0001522746,0.0005483096,0.001052879,0.0001458844],"domain_scores_gemma":[0.9914721,0.005829002,0.0006031014,0.001214282,0.0007775034,0.000104091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002104376,0.0001325924,0.001990719,0.0005262169,0.0006147905,0.0002933292,0.0002236947,0.462124,0.01395608,0.2560816,0.007694669,0.2561518],"study_design_scores_gemma":[0.000016109,0.0000531074,0.0003701578,0.00001847727,0.00003613023,0.00007882467,0.00001032324,0.9592419,0.003061073,0.03175639,0.005323541,0.00003386982],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006620636,0.0001067524,0.9988049,0.00003898602,0.00002231412,0.00001089229,0.00002797403,0.0001740321,0.0001520228],"genre_scores_gemma":[0.07945432,0.0006264609,0.9166477,0.0002318436,0.0002813128,0.0002865162,0.0004856049,0.0003941121,0.001592152],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006689254,"threshold_uncertainty_score":0.03537655,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2052813455","doi":"10.4236/ojs.2014.47050","title":"HAC-Robust Measurement of the Duration of a Trendless Subsample in a Global Climate Time Series","year":2014,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Climate variability and models","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"","keywords":"Hiatus; Heteroscedasticity; Series (stratigraphy); Autocorrelation; Estimator; Econometrics; Consistency (knowledge bases); Statistics; Duration (music); Climatology; Mathematics; Variance (accounting); Time series; Environmental science; Geology; Economics","authors":[{"name":"Ross McKitrick","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03619715538828634,"gpt":0.2564996501198835,"spread":0.2203024947315972,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00906847,0.0003505413,0.0006719761,0.002212836,0.0006079053,0.001045081,0.000989033,0.0009457447,0.002059661],"category_scores_gemma":[0.04404947,0.0002407489,0.0008243262,0.002512831,0.0007004968,0.001064769,0.001073454,0.001423751,0.0005158143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006597479,"about_ca_system_score_gemma":0.0008822074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005902132,"about_ca_topic_score_gemma":0.006849017,"domain_scores_codex":[0.9960366,0.001077489,0.0003268725,0.001465019,0.0008826939,0.0002113929],"domain_scores_gemma":[0.9692807,0.01400432,0.005002698,0.008226318,0.003095827,0.0003900215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008317599,0.0003089601,0.3475094,0.0007377085,0.00184893,0.0004161487,0.001323583,0.04874341,0.02318269,0.06366119,0.01689441,0.4945419],"study_design_scores_gemma":[0.00006922787,0.0005925308,0.6610258,0.0001621858,0.0003394363,0.0007283762,0.0004610209,0.2550193,0.01690197,0.03303316,0.03137393,0.0002931889],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.274102,0.001395342,0.7080234,0.0005421688,0.0003287307,0.0002266258,0.008935877,0.00127455,0.005171332],"genre_scores_gemma":[0.8800052,0.0002772987,0.1065064,0.0002065352,0.0002991288,0.000472231,0.00992287,0.0002470249,0.002063321],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00906847,"threshold_uncertainty_score":0.04795927,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2012014667","doi":"10.4236/ojs.2015.53021","title":"Trace of the Wishart Matrix and Applications","year":2015,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Moncton","funders":"","keywords":"Wishart distribution; TRACE (psycholinguistics); Matrix normal distribution; Matrix (chemical analysis); Inverse-Wishart distribution; Mathematics; Computer science; Statistics; Multivariate statistics; Philosophy","authors":[{"name":"T. Pham‐Gia","is_ca":true},{"name":"Dinh Ngoc Thanh","is_ca":false},{"name":"Duong Thanh Phong","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1918228468040818,"gpt":0.483363197339608,"spread":0.2915403505355262,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003578656,0.001334027,0.001325328,0.003076281,0.0007676284,0.003135059,0.001855048,0.001969609,0.006367283],"category_scores_gemma":[0.0277064,0.0006216211,0.001453293,0.004072802,0.003781994,0.004434542,0.002646369,0.003706179,0.002092949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001380267,"about_ca_system_score_gemma":0.001208777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002660878,"about_ca_topic_score_gemma":0.001185551,"domain_scores_codex":[0.9977957,0.0008712963,0.000175585,0.0003981284,0.0006382351,0.0001210504],"domain_scores_gemma":[0.9864926,0.009734339,0.0006584156,0.0008996677,0.001812005,0.0004030424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000346739,0.00003587713,0.0006994571,0.000252177,0.00003823901,0.0002368896,0.0002140044,0.02147456,0.001175835,0.9409269,0.003071585,0.03183971],"study_design_scores_gemma":[0.00000750353,0.00002514676,0.0003206126,0.00008077125,0.00001529497,0.0002953267,0.00005655858,0.08839773,0.0005604864,0.9017752,0.008432912,0.00003245511],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008051251,0.01790323,0.9535179,0.001441985,0.0005033308,0.00002980061,0.0001839177,0.0003340129,0.01803455],"genre_scores_gemma":[0.5161123,0.06425241,0.37428,0.00203272,0.006032662,0.0003512867,0.0007515589,0.001264526,0.0349225],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006367283,"threshold_uncertainty_score":0.02130073,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2475118633","doi":"10.4236/ojs.2016.63045","title":"Inverse Problem for a Time-Series Valued Computer Simulator via Scalarization","year":2016,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Acadia University","funders":"Acadia University","keywords":"Computer science; Inverse; Focus (optics); Set (abstract data type); Simulation; Series (stratigraphy); Inverse problem; Mathematical optimization; Algorithm; Scalar (mathematics); Applied mathematics; Mathematics; Mathematical analysis","authors":[{"name":"Pritam Ranjan","is_ca":false},{"name":"Mark R. Thomas","is_ca":true},{"name":"Holger Teismann","is_ca":true},{"name":"Sujay Mukhoti","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01456073951975799,"gpt":0.2751931832559599,"spread":0.2606324437362019,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002442928,0.0005986021,0.0007025239,0.0003417232,0.0002191268,0.0007527589,0.0005570262,0.0009554274,0.0027069],"category_scores_gemma":[0.007253648,0.0003246395,0.0005799278,0.0003014377,0.001265595,0.001215685,0.0009504484,0.001247942,0.0003478127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007295888,"about_ca_system_score_gemma":0.001013654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001184607,"about_ca_topic_score_gemma":0.0006713226,"domain_scores_codex":[0.9989598,0.0004555811,0.00004440989,0.0001912308,0.0003078166,0.0000411026],"domain_scores_gemma":[0.9967615,0.002437003,0.0002379146,0.0002040367,0.0003146555,0.00004497218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001738111,0.00005466706,0.0007639423,0.0001772169,0.00004090514,0.00006887431,0.0001141132,0.9070219,0.01174947,0.03917009,0.0004510495,0.04021392],"study_design_scores_gemma":[0.00001314124,0.00009888956,0.0001633911,0.000007205764,0.000009024488,0.00003774291,0.00001067492,0.9873542,0.003227885,0.008427852,0.000641073,0.000008944196],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005740351,0.0000297777,0.9933489,0.00009801012,0.000007067795,0.00002810148,0.00001287262,0.00007823011,0.0006566871],"genre_scores_gemma":[0.5995992,0.0001673864,0.3951968,0.0001498252,0.0000452501,0.0002895279,0.0001297539,0.0001160613,0.004306203],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0027069,"threshold_uncertainty_score":0.0129196,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2968975871","doi":"10.4236/ojs.2019.94031","title":"Using Excel to Explore the Effects of Assumption Violations on One-Way Analysis of Variance (ANOVA) Statistical Procedures","year":2019,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Variance (accounting); Heteroscedasticity; Microsoft excel; Statistical analysis; Statistical model; Statistics; Data mining; Machine learning; Econometrics; Mathematics","authors":[{"name":"W. H. Laverty","is_ca":true},{"name":"I. W. Kelly","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06967906361789952,"gpt":0.3327678796400093,"spread":0.2630888160221098,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02115211,0.00150505,0.00110723,0.003224554,0.0007360915,0.00255413,0.001847541,0.001174783,0.01230692],"category_scores_gemma":[0.09892789,0.000620527,0.001176749,0.003870942,0.001071034,0.002556351,0.001714695,0.004128644,0.00245511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006175761,"about_ca_system_score_gemma":0.00163152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001056977,"about_ca_topic_score_gemma":0.001014948,"domain_scores_codex":[0.986907,0.006560348,0.001642976,0.000924565,0.003667974,0.0002972262],"domain_scores_gemma":[0.7803231,0.2021368,0.004918185,0.007096836,0.005188612,0.0003364294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001549256,0.00221077,0.02858755,0.004852891,0.001162502,0.003194497,0.007367497,0.05840203,0.03262804,0.142975,0.1054085,0.6116614],"study_design_scores_gemma":[0.0003804744,0.004197788,0.04098004,0.002540471,0.0006576887,0.004309817,0.004107001,0.4168257,0.09111305,0.2259711,0.2081395,0.000777416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.029931,0.0003036391,0.9394253,0.0005641939,0.0003970963,0.001020878,0.003636031,0.01334504,0.01137676],"genre_scores_gemma":[0.07001836,0.0003376474,0.9224443,0.0003658849,0.00007696189,0.002474291,0.0009434821,0.001771833,0.001567164],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02115211,"threshold_uncertainty_score":0.1118644,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2012324263","doi":"10.4236/ojs.2011.12011","title":"Distributions of Ratios: From Random Variables to Random Matrices","year":2011,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Advanced Combinatorial Mathematics","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Random variable; Statistics; Applied mathematics; Sum of normally distributed random variables; Distribution (mathematics); Probability density function; Multivariate random variable; Mathematical analysis","authors":[{"name":"T. Pham‐Gia","is_ca":true},{"name":"N. Turkkan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06628427761356873,"gpt":0.335975448819036,"spread":0.2696911712054673,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006865566,0.001315648,0.0009797697,0.00406938,0.0006840706,0.004744643,0.002291876,0.002016171,0.007639404],"category_scores_gemma":[0.05114844,0.0008362293,0.0009539338,0.002871594,0.00521093,0.01026993,0.002613093,0.003420582,0.00268179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001300382,"about_ca_system_score_gemma":0.0005956895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006226012,"about_ca_topic_score_gemma":0.0002642847,"domain_scores_codex":[0.9944341,0.003498495,0.0002064697,0.0007508851,0.0008650637,0.0002450009],"domain_scores_gemma":[0.9755387,0.01893657,0.002032202,0.001655725,0.001315985,0.0005208887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002303234,0.000009302403,0.000314018,0.0000542303,0.000009100241,0.0000667971,0.0001255163,0.005663409,0.0003525004,0.9819935,0.001297556,0.01009094],"study_design_scores_gemma":[0.00001218105,0.0000248817,0.0002660431,0.0000449599,0.000006369663,0.0001949752,0.00004937253,0.03247074,0.0002937604,0.962148,0.00446705,0.00002179704],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02024292,0.003961573,0.9594899,0.001914605,0.0002096424,0.00008802286,0.0004554395,0.0003722789,0.01326562],"genre_scores_gemma":[0.6437784,0.01382437,0.3151591,0.002429014,0.00296516,0.001067744,0.0011892,0.0009119728,0.01867512],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007639404,"threshold_uncertainty_score":0.036309,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2545722099","doi":"10.4236/ojs.2016.65078","title":"Hypergeometric Functions: From One Scalar Variable to Several Matrix Arguments, in Statistics and Beyond","year":2016,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Random Matrices and Applications","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Moncton","funders":"Université de Moncton","keywords":"Hypergeometric function of a matrix argument; Hypergeometric distribution; Hypergeometric function; Mathematics; Generalized hypergeometric function; Confusion; Basic hypergeometric series; Scalar (mathematics); Hypergeometric identity; Statistics; Matrix (chemical analysis); Univariate; Algebra over a field; Pure mathematics; Psychology; Multivariate statistics","authors":[{"name":"T. Pham‐Gia","is_ca":true},{"name":"Dinh Ngoc Thanh","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03275803646155259,"gpt":0.323125225805209,"spread":0.2903671893436565,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002658503,0.001085827,0.0009414025,0.003889136,0.001440953,0.004374461,0.0008906628,0.002164728,0.003526358],"category_scores_gemma":[0.007353883,0.0003597181,0.0006632358,0.005070192,0.00705039,0.009425608,0.001829666,0.004413081,0.001532462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001629486,"about_ca_system_score_gemma":0.0009878046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009244406,"about_ca_topic_score_gemma":0.0005142424,"domain_scores_codex":[0.9986836,0.000656654,0.00006384002,0.0002052643,0.0002999975,0.00009057735],"domain_scores_gemma":[0.9973807,0.001823828,0.0002177409,0.0001953063,0.0002556179,0.0001268717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000006282102,0.000005142209,0.00011025,0.00006491548,0.00000447166,0.00004745525,0.0001821776,0.0003741713,0.0001554126,0.9884631,0.00199125,0.008595191],"study_design_scores_gemma":[0.000001696438,0.000009049821,0.0001454283,0.00006254669,0.000004071177,0.0001037136,0.00007969263,0.0009644,0.00008898296,0.9793468,0.01918541,0.000008188536],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03770763,0.2810281,0.4961347,0.03391822,0.004874023,0.0000492835,0.0004149202,0.0004160172,0.1454571],"genre_scores_gemma":[0.6231378,0.1890611,0.11809,0.01306527,0.0201521,0.000198072,0.0003067293,0.0005630877,0.03542587],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004374461,"threshold_uncertainty_score":0.01405966,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3008678529","doi":"10.4236/ojs.2020.101008","title":"Mean Absolute Deviations about the Mean, the Cut Norm and Taxicab Correspondence Analysis","year":2020,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Sensory Analysis and Statistical Methods","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Moncton","funders":"","keywords":"Mathematics; Standard deviation; Maximization; Least absolute deviations; Statistics; Absolute deviation; Minification; Large deviations theory; Norm (philosophy); Combinatorics; Mathematical optimization; Estimator","authors":[{"name":"Vartan Choulakian","is_ca":true},{"name":"Ghassan Abou‐Samra","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09323538382250615,"gpt":0.3267937122476653,"spread":0.2335583284251592,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006759031,0.0008608629,0.001390966,0.003320404,0.001034555,0.0029104,0.001212844,0.00144881,0.001999495],"category_scores_gemma":[0.03154496,0.000490991,0.000944413,0.003193564,0.003831453,0.002600379,0.002207946,0.002141704,0.000718625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001322134,"about_ca_system_score_gemma":0.001644749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001341964,"about_ca_topic_score_gemma":0.001291697,"domain_scores_codex":[0.9946799,0.001774497,0.0003124425,0.001338714,0.001684288,0.0002102366],"domain_scores_gemma":[0.9848753,0.009636068,0.001855688,0.001957304,0.001318701,0.0003569399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007246987,0.0001978894,0.01334433,0.0004522032,0.0003314348,0.0002748766,0.0006549645,0.2953115,0.01813978,0.3279046,0.005007777,0.337656],"study_design_scores_gemma":[0.00003005684,0.0002160875,0.008441633,0.00007460282,0.00004869419,0.0003649794,0.0002077747,0.6997429,0.007698188,0.2779056,0.005175648,0.00009401657],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03009329,0.0003697588,0.9669452,0.000229977,0.00003716872,0.00005758001,0.000195576,0.0002269552,0.001844552],"genre_scores_gemma":[0.4423535,0.0004242614,0.5524257,0.0001938395,0.0001478593,0.0005548901,0.0008208487,0.0004231797,0.002655929],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006759031,"threshold_uncertainty_score":0.03574562,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4210672984","doi":"10.4236/ojs.2022.121001","title":"Quasi-Binomial Regression Model for the Analysis of Data with Extra-Binomial Variation","year":2022,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Binomial regression; Negative binomial distribution; Mathematics; Statistics; Count data; Quasi-likelihood; Binomial distribution; Beta-binomial distribution; Continuity correction; Binomial test; Binary data; Binomial proportion confidence interval; Regression analysis; Econometrics; Binary number; Poisson distribution","authors":[{"name":"Mohamed M. Shoukri","is_ca":true},{"name":"Maha Al-Eid","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2047915268104073,"gpt":0.4382070536553679,"spread":0.2334155268449606,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05130262,0.001364155,0.002344271,0.001881518,0.000894253,0.002186863,0.00519579,0.001923031,0.01929579],"category_scores_gemma":[0.09831228,0.0009550952,0.002629991,0.003141357,0.002742655,0.003457146,0.002262909,0.004638855,0.004198985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002103773,"about_ca_system_score_gemma":0.003600622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003594849,"about_ca_topic_score_gemma":0.003100799,"domain_scores_codex":[0.9511634,0.04018616,0.001087678,0.002810966,0.00424226,0.0005095577],"domain_scores_gemma":[0.8903984,0.09543043,0.00484291,0.004591397,0.004225555,0.0005112544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002224677,0.0001238426,0.003734451,0.001137135,0.0004047866,0.0004620802,0.0009211962,0.05946992,0.001430194,0.8325858,0.01003894,0.08946914],"study_design_scores_gemma":[0.0001014912,0.0002840931,0.002085963,0.0003623304,0.0001127776,0.0004578845,0.0001443943,0.5216029,0.000485915,0.4504149,0.02385338,0.00009394726],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007652527,0.0002263008,0.997691,0.0001735577,0.00006637534,0.0001703973,0.0001534132,0.0001247068,0.0006290422],"genre_scores_gemma":[0.04296618,0.001003051,0.9455495,0.0004724195,0.0002328485,0.004184166,0.0007617628,0.0002401455,0.00458991],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05130262,"threshold_uncertainty_score":0.2713174,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1997376302","doi":"10.4236/ojs.2012.25067","title":"Effective Truncation of a Student’s &amp;lt;i&amp;gt;t&amp;lt;/i&amp;gt;-Distribution by Truncation of the Chi Distribution in a Chi-Normal Mixture","year":2012,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Kurtosis; Truncation (statistics); Mathematics; Student's t-distribution; Normal distribution; Distribution (mathematics); Variance-gamma distribution; Inverse-chi-squared distribution; Truncated normal distribution; Statistics; F-distribution; Asymptotic distribution; Mathematical analysis; Exponential distribution; Probability distribution; Distribution fitting; Econometrics; Estimator; Autoregressive conditional heteroskedasticity","authors":[{"name":"Daniel T. Cassidy","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06311558512117567,"gpt":0.4151881734304895,"spread":0.3520725883093139,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01263258,0.001197348,0.001698521,0.001724962,0.001093792,0.003338458,0.002977801,0.001970552,0.01094134],"category_scores_gemma":[0.05151036,0.0009336963,0.001832075,0.001651108,0.004409301,0.006040959,0.003595517,0.005143772,0.00380952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003056852,"about_ca_system_score_gemma":0.0028428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002031673,"about_ca_topic_score_gemma":0.00194378,"domain_scores_codex":[0.9926443,0.002141374,0.0004136857,0.001202265,0.002904664,0.0006936659],"domain_scores_gemma":[0.9709046,0.01692407,0.001774608,0.005983469,0.003551416,0.0008618573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005364845,0.0002113655,0.009184736,0.0003608539,0.0001636799,0.001709726,0.001489012,0.1084529,0.02514091,0.7229955,0.006765073,0.1229898],"study_design_scores_gemma":[0.00006597878,0.0002451272,0.005685053,0.0001920803,0.00009930938,0.001813664,0.0003049996,0.5798298,0.01830771,0.3806132,0.01263804,0.0002050238],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01877236,0.0001824,0.9750971,0.0002524156,0.0001157979,0.00005880971,0.00008750203,0.0006171983,0.004816419],"genre_scores_gemma":[0.5315586,0.0009166538,0.4409808,0.0008457861,0.0002801644,0.0006119231,0.0009765131,0.001665011,0.02216447],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01263258,"threshold_uncertainty_score":0.06680828,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2044890887","doi":"10.4236/ojs.2013.34030","title":"Change-Point Detection for General Nonparametric Regression Models","year":2013,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Mathematics; Nonparametric regression; Nonparametric statistics; Statistics; Regression analysis; Covariate; Regression; Bounded function; Applied mathematics; Mathematical analysis","authors":[{"name":"Murray D. Burke","is_ca":true},{"name":"Gildas Bewa","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2577878223394403,"gpt":0.4240849277098376,"spread":0.1662971053703973,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03439382,0.001842219,0.00336049,0.005294848,0.0009928065,0.002120624,0.005144041,0.003660071,0.00279814],"category_scores_gemma":[0.1604656,0.001174378,0.002672239,0.004827623,0.005097064,0.003757425,0.004253684,0.004905336,0.0008955329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001222197,"about_ca_system_score_gemma":0.001874824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001104425,"about_ca_topic_score_gemma":0.0007616672,"domain_scores_codex":[0.9798573,0.01281916,0.0008379967,0.003003143,0.002914099,0.0005683103],"domain_scores_gemma":[0.8693206,0.1096944,0.008403731,0.007035561,0.004622568,0.0009231923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005731761,0.0003358031,0.009926989,0.001147289,0.0008514323,0.001329279,0.0005228502,0.3078655,0.005507908,0.4150451,0.005335205,0.2515595],"study_design_scores_gemma":[0.0000425664,0.0001621282,0.001145121,0.00004906115,0.00005894647,0.0003239188,0.00003412109,0.8336682,0.001121979,0.1614172,0.001918859,0.00005786475],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002622365,0.0002494525,0.9965336,0.0001122144,0.00002996356,0.00005321418,0.00003815102,0.0001602651,0.0002008006],"genre_scores_gemma":[0.2903621,0.001457997,0.7018306,0.000518928,0.0004802546,0.001462143,0.0008043902,0.0002762228,0.002807359],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03439382,"threshold_uncertainty_score":0.1818941,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2969575993","doi":"10.4236/ojs.2019.94035","title":"On the Index of Repeatability: Estimation and Sample Size Requirements","year":2019,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Repeatability; Statistics; Sample size determination; Variance (accounting); Estimator; Mathematics; Sample (material); Index (typography); Computer science","authors":[{"name":"Maha Al-Eid","is_ca":false},{"name":"Mohamed M. Shoukri","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.4968311130426175,"gpt":0.56086270556895,"spread":0.06403159252633256,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1274707,0.001180277,0.002821924,0.002630172,0.0008916487,0.00165611,0.002908796,0.003317234,0.002214053],"category_scores_gemma":[0.4312887,0.0006640279,0.001587939,0.002487965,0.002641702,0.002648436,0.002667222,0.002774276,0.0007106568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001276795,"about_ca_system_score_gemma":0.0026602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008941951,"about_ca_topic_score_gemma":0.0007991231,"domain_scores_codex":[0.8416047,0.12758,0.007458827,0.00731304,0.01539254,0.0006508416],"domain_scores_gemma":[0.4401194,0.5133483,0.01004782,0.02210084,0.01364192,0.0007417354],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00333079,0.00061732,0.06052701,0.003606942,0.001399042,0.001828086,0.001720859,0.08081491,0.02179778,0.1785837,0.01603383,0.6297397],"study_design_scores_gemma":[0.001501714,0.007403791,0.09472097,0.0025139,0.001531258,0.006484964,0.0009795491,0.4863151,0.04383884,0.3028089,0.05125612,0.0006448999],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01246411,0.001784129,0.9791752,0.001784746,0.0002236266,0.001465508,0.0006284851,0.0002394123,0.002234807],"genre_scores_gemma":[0.1346899,0.0009469069,0.8548358,0.0007174358,0.0003942303,0.006668374,0.0007982612,0.0002268067,0.0007223108],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8725293,"threshold_uncertainty_score":0.6741377,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2087268427","doi":"10.4236/ojs.2013.36a005","title":"Inference for the Normal Mean with Known Coefficient of Variation","year":2013,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Estimator; Mathematics; Inference; Statistic; Statistics; Sample size determination; Point estimation; Statistical inference; Applied mathematics; Exponential family; Variation (astronomy); Computer science; Artificial intelligence","authors":[{"name":"Yuejiao Fu","is_ca":true},{"name":"Hangjing Wang","is_ca":true},{"name":"Augustine Wong","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0971537910778619,"gpt":0.3822120823949879,"spread":0.285058291317126,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01806498,0.0007141723,0.002275444,0.003019826,0.0005497361,0.001747738,0.002425192,0.002025748,0.001552],"category_scores_gemma":[0.1235959,0.0005346503,0.001769179,0.001840843,0.002524646,0.003703519,0.001901755,0.002981727,0.0004981685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009644896,"about_ca_system_score_gemma":0.001459143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001144209,"about_ca_topic_score_gemma":0.0008676986,"domain_scores_codex":[0.9883001,0.005752661,0.0006145103,0.002789971,0.002163944,0.0003788788],"domain_scores_gemma":[0.9216793,0.06475669,0.00388266,0.005455235,0.003788497,0.0004375721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003169998,0.0001722848,0.0252717,0.0006608583,0.0006266435,0.0008068427,0.0006774226,0.2002902,0.009649985,0.4686143,0.00309055,0.2898223],"study_design_scores_gemma":[0.00004711487,0.0001724219,0.005801613,0.0001029428,0.00009958991,0.000587285,0.0001028732,0.6831458,0.004269558,0.3028292,0.002742434,0.00009916976],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00659146,0.0001539778,0.9927763,0.00007455025,0.0000241719,0.00002295943,0.0000428051,0.00009363341,0.0002201839],"genre_scores_gemma":[0.4225108,0.0009368239,0.5732573,0.0002489636,0.0002830419,0.0003893653,0.0006817477,0.000129937,0.001562011],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01806498,"threshold_uncertainty_score":0.09553784,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2991299027","doi":"10.4236/ojs.2019.96040","title":"Likelihood Methods for Basic Stratified Sampling, with Application to Von Bertalanffy Growth Model Estimation","year":2019,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"Canada First Research Excellence Fund; Ocean Frontier Institute; Natural Sciences and Engineering Research Council of Canada; Memorial University of Newfoundland","keywords":"Statistics; Estimator; Stratified sampling; Sampling (signal processing); Maximum likelihood; Mathematics; Computer science; Marginal likelihood","authors":[{"name":"Nan Zheng","is_ca":true},{"name":"Noel G. Cadigan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06901775248005243,"gpt":0.4414852496311544,"spread":0.3724674971511019,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01562249,0.001054827,0.001272346,0.001927973,0.0006677305,0.001174031,0.002399654,0.001211245,0.00299544],"category_scores_gemma":[0.05991023,0.0009791562,0.001472191,0.002166157,0.001597011,0.001840064,0.00248412,0.002420687,0.0008165953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001330365,"about_ca_system_score_gemma":0.002501655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005342014,"about_ca_topic_score_gemma":0.004787584,"domain_scores_codex":[0.9937252,0.004904042,0.0002226258,0.0003569897,0.000670813,0.0001202761],"domain_scores_gemma":[0.9805064,0.01615829,0.0007323807,0.001230065,0.001191564,0.0001812842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001408807,0.00007182317,0.003945285,0.0004247579,0.0002485152,0.00023429,0.0004602504,0.2661569,0.00200135,0.5574085,0.003267934,0.1656396],"study_design_scores_gemma":[0.00003353465,0.00003304505,0.0007946087,0.00005657492,0.0000298324,0.00008652533,0.00002999143,0.7309111,0.0005764341,0.262421,0.004996399,0.00003100144],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007827894,0.0001300668,0.998683,0.00006005051,0.00001142307,0.00003139284,0.00003680061,0.00006153721,0.0002028929],"genre_scores_gemma":[0.04479411,0.0005992239,0.9521514,0.0001043544,0.0001004214,0.0005821014,0.0003829158,0.0001563199,0.001129091],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01562249,"threshold_uncertainty_score":0.08262062,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2792040161","doi":"10.4236/ojs.2018.81012","title":"Simulated Minimum Hellinger Distance Inference Methods for Count Data","year":2018,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval; Ontario Universities’ Application Centre","funders":"","keywords":"Hellinger distance; Mathematics; Count data; Goodness of fit; Parametric statistics; Statistics; Robustness (evolution); Homogeneity (statistics); Inference; Applied mathematics; Algorithm; Computer science; Poisson distribution; Artificial intelligence","authors":[{"name":"Andrew Luong","is_ca":true},{"name":"Claire Bilodeau","is_ca":true},{"name":"Christopher Blier-Wong","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.380619580975107,"gpt":0.5567857153716702,"spread":0.1761661343965633,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01538295,0.0008597112,0.001754263,0.002277336,0.0009420656,0.001824965,0.003635957,0.001806349,0.002523276],"category_scores_gemma":[0.08326495,0.0006394705,0.0013946,0.001909432,0.00305225,0.00420832,0.003409236,0.002438629,0.0005278672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001400874,"about_ca_system_score_gemma":0.001336624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009860862,"about_ca_topic_score_gemma":0.0007455255,"domain_scores_codex":[0.9857317,0.01033162,0.000567431,0.001525449,0.001626535,0.0002173066],"domain_scores_gemma":[0.9215818,0.06606039,0.003849708,0.00595072,0.002080678,0.0004767084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000176524,0.00008001897,0.00599884,0.0003716419,0.0003797437,0.0002314026,0.0003523539,0.3073648,0.000865058,0.6105728,0.001221922,0.07238495],"study_design_scores_gemma":[0.00002622108,0.00007316599,0.0006166701,0.00005374396,0.00003273961,0.0001218393,0.00005294108,0.6009226,0.001021523,0.3945173,0.002525995,0.00003527564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005046518,0.0002319604,0.9940009,0.0001161986,0.00002913538,0.00004208912,0.00006657984,0.00004966855,0.0004168633],"genre_scores_gemma":[0.2592779,0.0007140301,0.7361236,0.0002903049,0.0002159703,0.0005673119,0.0007442984,0.00009422313,0.001972247],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01538295,"threshold_uncertainty_score":0.08135378,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2968687647","doi":"10.4236/ojs.2019.94032","title":"Demographic Expansion and Contraction in a Neotropical Fish during the Late Pleistocene-Holocene","year":2019,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Fish biology, ecology, and behavior","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"Ministério do Meio Ambiente; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Holocene; Pleistocene; Population; Demographic history; Last Glacial Maximum; Ecology; Phylogeography; Biology; Geology; Paleontology; Demography; Genetic variation; Phylogenetics","authors":[{"name":"Carolina Lemes Nascimento Costa","is_ca":false},{"name":"S. Iván Pérez","is_ca":false},{"name":"José Louvise","is_ca":false},{"name":"Carlos Henrique Tonhatti","is_ca":false},{"name":"Rute B. G. Clemente‐Carvalho","is_ca":true},{"name":"Ana Cristina Petry","is_ca":false},{"name":"Sérgio F. dos Reis","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01248177261082343,"gpt":0.2526643676248738,"spread":0.2401825950140503,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003638763,0.0001041511,0.00009054974,0.0006349751,0.0002034307,0.0001919586,0.0001279584,0.0001065699,0.0006228802],"category_scores_gemma":[0.001068688,0.00008888814,0.0001350264,0.0005115084,0.0002945867,0.000161974,0.0002260172,0.0001534563,0.0000773593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002592287,"about_ca_system_score_gemma":0.0002027918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006671209,"about_ca_topic_score_gemma":0.00968715,"domain_scores_codex":[0.9999192,0.00001755404,0.000006619989,0.00003012715,0.0000160329,0.00001037109],"domain_scores_gemma":[0.9996703,0.00007129727,0.0001266799,0.0000283033,0.00006379092,0.00003965245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001016836,0.000011582,0.9778855,0.00002771758,0.00003873634,0.0001018144,0.0006752027,0.000943656,0.007503984,0.0001628284,0.00009089884,0.01245636],"study_design_scores_gemma":[0.000001776798,0.00001042494,0.9989346,0.000002215924,0.000004736904,0.00004734331,0.00009741706,0.0005788091,0.0001149986,0.00004339299,0.0001627342,0.000001640471],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995713,0.0000625821,0.0001029992,0.00001053444,7.57523e-7,8.885443e-7,0.00005003146,0.000003023398,0.0001980487],"genre_scores_gemma":[0.9995576,0.00007013515,0.0001583773,0.000004746978,0.000001639766,0.000002218332,0.0001171444,0.000001350711,0.00008685215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006671209,"threshold_uncertainty_score":0.01326478,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1978696365","doi":"10.4236/ojs.2011.13018","title":"Revisit the Two Sample t-Test with a Known Ratio of Variances","year":2011,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Statistics; Mathematics; Likelihood-ratio test; Inference; Sample size determination; Sample (material); Levene's test; Computer science; Artificial intelligence","authors":[{"name":"Yongxiu She","is_ca":true},{"name":"Augustine Wong","is_ca":true},{"name":"Xiaofeng Zhou","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2083267799212133,"gpt":0.4359756614557054,"spread":0.2276488815344921,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0299041,0.001563532,0.002671215,0.002779709,0.0009402995,0.002461425,0.004232636,0.003801219,0.006848462],"category_scores_gemma":[0.1581597,0.0006368024,0.002548528,0.00277832,0.004454426,0.005579507,0.00269419,0.006912262,0.002788259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00110587,"about_ca_system_score_gemma":0.00217757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001375097,"about_ca_topic_score_gemma":0.001006072,"domain_scores_codex":[0.9702527,0.0179506,0.001189854,0.005634182,0.004471245,0.0005014625],"domain_scores_gemma":[0.8558247,0.1198241,0.005446005,0.01171247,0.00642223,0.0007704309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006065228,0.0004460778,0.01281196,0.001197803,0.00111093,0.001439846,0.001061129,0.05099117,0.009271033,0.3321576,0.01122653,0.5776793],"study_design_scores_gemma":[0.0002284354,0.001037722,0.007622129,0.0003279056,0.0004188473,0.002439722,0.0003684323,0.4352724,0.008378327,0.5199738,0.02363448,0.0002978549],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004001139,0.0003261097,0.9937708,0.0003659652,0.0002813628,0.00006560535,0.00008625041,0.0002237829,0.0008789633],"genre_scores_gemma":[0.2025519,0.0006289568,0.7896885,0.001081911,0.001133041,0.0006015925,0.0004724796,0.000422426,0.003419156],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0299041,"threshold_uncertainty_score":0.1581499,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2221432182","doi":"10.4236/ojs.2015.57068","title":"Statistical Classification Using the Maximum Function","year":2015,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Moncton","funders":"","keywords":"Linear discriminant analysis; Cluster analysis; Discriminant function analysis; Mathematics; Extension (predicate logic); Function (biology); Pattern recognition (psychology); Statistical hypothesis testing; Computer science; Artificial intelligence; Statistics; Algorithm","authors":[{"name":"T. Pham‐Gia","is_ca":true},{"name":"Nguyen Dac Nhat","is_ca":false},{"name":"Nguyen V. Phong","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1598425714878807,"gpt":0.3533299544459751,"spread":0.1934873829580945,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004996874,0.00109371,0.001680552,0.004333501,0.001099641,0.003305778,0.001769729,0.002106824,0.003421341],"category_scores_gemma":[0.01521102,0.0005120272,0.001542416,0.003435458,0.003143959,0.004663635,0.002874411,0.002529789,0.002186703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001048918,"about_ca_system_score_gemma":0.001061397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006059743,"about_ca_topic_score_gemma":0.0002984969,"domain_scores_codex":[0.9967933,0.001502842,0.0001936751,0.0005484868,0.0007711878,0.0001904952],"domain_scores_gemma":[0.9947385,0.003748842,0.0003856225,0.0006224353,0.0003850195,0.0001195938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002101851,0.00006479297,0.002029466,0.0004031006,0.0001341443,0.0001684563,0.0002909814,0.1029224,0.005474414,0.5292936,0.007256856,0.3517516],"study_design_scores_gemma":[0.0000145615,0.00005917282,0.0009128505,0.00008816641,0.00002678425,0.0002113405,0.00003512885,0.5596225,0.003202158,0.4257288,0.01005027,0.0000482797],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003023781,0.0006909095,0.9938112,0.0002330349,0.00004007027,0.00002048343,0.0000807921,0.0003409493,0.001758736],"genre_scores_gemma":[0.2550139,0.002134652,0.7371047,0.0004143522,0.0006907486,0.0004647905,0.0005669473,0.0003972521,0.003212661],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004996874,"threshold_uncertainty_score":0.02642637,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2753173657","doi":"10.4236/ojs.2017.74052","title":"Simulated Minimum Hellinger Distance Estimation for Some Continuous Financial and Actuarial Models","year":2017,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval; Ontario Universities’ Application Centre","funders":"","keywords":"Hellinger distance; Estimator; Consistency (knowledge bases); Mathematics; Probability density function; Closed-form expression; Applied mathematics; Expression (computer science); Maximization; Density estimation; Function (biology); Mathematical optimization; Statistics; Computer science; Mathematical analysis","authors":[{"name":"Andrew Luong","is_ca":true},{"name":"Claire Bilodeau","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06807495672095115,"gpt":0.2950093762669844,"spread":0.2269344195460333,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005152571,0.000444374,0.0009139011,0.0008706847,0.0003804602,0.0009940871,0.001245383,0.001220996,0.001365884],"category_scores_gemma":[0.02233121,0.0003492433,0.0007071223,0.000593988,0.001332294,0.00200091,0.001439754,0.001278806,0.0001400519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001372259,"about_ca_system_score_gemma":0.0008931525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003375533,"about_ca_topic_score_gemma":0.002149337,"domain_scores_codex":[0.9986181,0.0008775376,0.00006673077,0.000192393,0.0001695188,0.00007561234],"domain_scores_gemma":[0.9799961,0.01689525,0.001234854,0.0009838667,0.0005638541,0.0003260827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006836711,0.00002933909,0.001392099,0.00003776786,0.00003372741,0.00007723653,0.00007484486,0.9175864,0.0003002135,0.07237732,0.0003632874,0.007659412],"study_design_scores_gemma":[0.000004879646,0.00001047191,0.0001831032,0.000004346472,0.000002862939,0.00001640078,0.000005786688,0.9790468,0.0001347226,0.02044692,0.0001367892,0.000007004344],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1248145,0.0002704773,0.8726932,0.0005002687,0.00002686954,0.00004214071,0.0001320617,0.00008905132,0.001431412],"genre_scores_gemma":[0.8881044,0.0002196214,0.1093426,0.00006817155,0.00003232423,0.00008268968,0.0002627888,0.00003025706,0.001857164],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005152571,"threshold_uncertainty_score":0.02724969,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2765249720","doi":"10.4236/ojs.2017.75058","title":"Simulated Minimum Cram&amp;#233;r-Von Mises Distance Estimation for Some Actuarial and Financial Models","year":2017,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval; Actua","funders":"","keywords":"Estimator; Mathematics; Hellinger distance; Density estimation; Probability density function; Applied mathematics; Poisson distribution; Mathematical optimization; Statistics","authors":[{"name":"Andrew Luong","is_ca":true},{"name":"Christopher Blier-Wong","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1025580147400975,"gpt":0.317185612322666,"spread":0.2146275975825684,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004397102,0.0004842156,0.0008878899,0.0009706194,0.0003451867,0.0007845362,0.00155999,0.001132845,0.00246194],"category_scores_gemma":[0.0186199,0.000439414,0.0008897871,0.0007599377,0.001075772,0.001876026,0.001583716,0.001718288,0.0003471666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001167889,"about_ca_system_score_gemma":0.001076096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003577527,"about_ca_topic_score_gemma":0.002859312,"domain_scores_codex":[0.9979913,0.001245276,0.00009238275,0.000282113,0.0002908889,0.00009800163],"domain_scores_gemma":[0.9889109,0.00854014,0.0007665983,0.0009924646,0.0005877685,0.0002020647],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007596243,0.00004252439,0.001612099,0.00008853078,0.00006420685,0.0001056522,0.00011434,0.7547761,0.00068227,0.201242,0.001130685,0.04006556],"study_design_scores_gemma":[0.000003854426,0.0000154054,0.0002056459,0.000008302687,0.000003764773,0.00002927913,0.000007710371,0.9570751,0.0002885583,0.04174059,0.0006121603,0.000009750988],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01603214,0.0002294629,0.9825467,0.0001921707,0.00001938642,0.00001426653,0.00004783246,0.00008174453,0.0008363677],"genre_scores_gemma":[0.6113957,0.0005421267,0.3828492,0.0001239729,0.00008333698,0.0001336023,0.0004207786,0.0001094805,0.004341895],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004397102,"threshold_uncertainty_score":0.02325439,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3121948562","doi":"10.4236/ojs.2021.111005","title":"Analysis of Length of Stay (LOS) Data from the Medical Records of Tertiary Care Hospital in Saudi Arabia for Five Diagnosis Related Groups: Application of Cox Prediction Model","year":2021,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Medicine; Medical record; Proportional hazards model; Emergency medicine; Hazard; Regression analysis; Medical emergency; Pediatrics; Internal medicine; Statistics","authors":[{"name":"Sara N. Algahtani","is_ca":false},{"name":"Mohamed M. Shoukri","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03144689886815968,"gpt":0.3392500363006075,"spread":0.3078031374324478,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005087861,0.0005468195,0.0005534432,0.002700304,0.000324688,0.0008468114,0.0007496322,0.0005187367,0.001581364],"category_scores_gemma":[0.01470914,0.0002447937,0.001388601,0.001903983,0.0001990474,0.0005816768,0.0005848157,0.0008698091,0.0002911166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009849609,"about_ca_system_score_gemma":0.001176628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01902743,"about_ca_topic_score_gemma":0.009008025,"domain_scores_codex":[0.9983634,0.0006424949,0.0001968709,0.0003339125,0.0002877948,0.0001755736],"domain_scores_gemma":[0.9848353,0.01045804,0.002213413,0.0008278351,0.001258655,0.0004068152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004341807,0.0001374598,0.9750039,0.00008506096,0.0002432578,0.0002164556,0.0002463474,0.01113883,0.0001529123,0.0002522795,0.0006687092,0.01142068],"study_design_scores_gemma":[0.00004608685,0.0006453234,0.642884,0.00007960465,0.0002557487,0.0005237234,0.0008797024,0.3521875,0.000634215,0.0006831234,0.001135894,0.00004514771],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906749,0.0002141744,0.005703607,0.0001683394,0.00001641556,0.00008274334,0.002792717,0.0000558841,0.0002911824],"genre_scores_gemma":[0.992227,0.0001417963,0.003320879,0.00001604341,0.00001560233,0.00006732438,0.003953741,0.000006554538,0.0002511106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01902743,"threshold_uncertainty_score":0.03783339,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3175869339","doi":"10.4236/ojs.2021.113026","title":"Inference Procedures on the Generalized Poisson Distribution from Multiple Samples: Comparisons with Nonparametric Models for Analysis of Covariance (ANCOVA) of Count Data","year":2021,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Count data; Mathematics; Negative binomial distribution; Poisson distribution; Statistics; Nonparametric statistics; Analysis of covariance; Zero-inflated model; Quasi-likelihood; Covariate; Goodness of fit; Poisson regression; Population","authors":[{"name":"Maha Al-Eid","is_ca":false},{"name":"Mohamed M. Shoukri","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2856032026145695,"gpt":0.4368913635636237,"spread":0.1512881609490542,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.08229309,0.001872944,0.002725616,0.003482994,0.001779269,0.002341216,0.004682994,0.002402412,0.003509949],"category_scores_gemma":[0.2454197,0.0009904088,0.003648064,0.003548851,0.004955662,0.004299061,0.00358854,0.005128052,0.0005699329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001564864,"about_ca_system_score_gemma":0.003919041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003214142,"about_ca_topic_score_gemma":0.002712657,"domain_scores_codex":[0.9242648,0.06501836,0.001514535,0.004040689,0.004611802,0.0005497525],"domain_scores_gemma":[0.793277,0.1826372,0.006998538,0.01256116,0.003926427,0.000599592],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000710541,0.0003331022,0.01498491,0.001201185,0.002132607,0.000710706,0.001984573,0.1465698,0.003964715,0.5575985,0.003870371,0.2659391],"study_design_scores_gemma":[0.0001538264,0.000487686,0.004284829,0.0002051358,0.0002583043,0.0004895497,0.0003375431,0.5151559,0.002771121,0.4709242,0.004793683,0.0001382699],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004304666,0.00009922864,0.9949617,0.00007442081,0.00003347471,0.0001171967,0.00005154055,0.0001305033,0.0002272133],"genre_scores_gemma":[0.08382257,0.000288643,0.9134668,0.0001484424,0.00009864315,0.001358823,0.0002268938,0.0001986726,0.0003905445],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08229309,"threshold_uncertainty_score":0.4352126,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2750166930","doi":"10.4236/ojs.2017.74047","title":"An Analysis of Fights in the National Hockey League","year":2017,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"League; TRIPS architecture; Football; Advertising; Test (biology); Ice hockey; Demographic economics; Geography; Aeronautics; Transport engineering; Engineering; Business; Economics; Archaeology; Medicine; Geology; Physical medicine and rehabilitation","authors":[{"name":"Henry L. Castillo","is_ca":false},{"name":"Paul M. Sommers","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09707962080463815,"gpt":0.3364671582031685,"spread":0.2393875373985303,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001112891,0.0002832197,0.0003043485,0.002257558,0.0004409802,0.00107559,0.0005125749,0.0003459065,0.00298411],"category_scores_gemma":[0.005429361,0.0001960794,0.0002947932,0.002169848,0.0003838845,0.0005651103,0.00078207,0.0005817591,0.0008539333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001064852,"about_ca_system_score_gemma":0.0007217746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06029012,"about_ca_topic_score_gemma":0.1056153,"domain_scores_codex":[0.9988921,0.0002353432,0.00007486229,0.0002018456,0.0003454445,0.0002503663],"domain_scores_gemma":[0.9941526,0.001560061,0.002160068,0.000239177,0.0008567265,0.001031336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001978135,0.0001296124,0.9896345,0.00001923796,0.000093254,0.0001316658,0.0004531332,0.0006983832,0.0002801372,0.0002678677,0.002709002,0.005385366],"study_design_scores_gemma":[0.000006883076,0.00008378852,0.9953135,0.00001153444,0.00001084347,0.00005456208,0.001306331,0.001745489,0.0001025438,0.00007532985,0.001282032,0.000007076399],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938498,0.00006276117,0.0003684228,0.00009272165,0.00001180353,0.00001652887,0.003863463,0.00001364119,0.001720808],"genre_scores_gemma":[0.9890639,0.00005630471,0.000244886,0.00002693403,0.00001626653,0.00002324207,0.008568561,0.000009320356,0.001990587],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06029012,"threshold_uncertainty_score":0.1198784,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2626987868","doi":"10.4236/ojs.2017.73033","title":"Maximum Entropy Empirical Likelihood Methods Based on Laplace Transforms for Nonnegative Continuous Distribution with Actuarial Applications","year":2017,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"","keywords":"Mathematics; Laplace distribution; Laplace transform; Applied mathematics; Principle of maximum entropy; Likelihood function; Exponential function; Mathematical optimization; Mellin transform; Maximum likelihood; Statistics; Mathematical analysis","authors":[{"name":"Andrew Luong","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1111574850337629,"gpt":0.462096501286016,"spread":0.3509390162522532,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004635142,0.001069302,0.00120945,0.001288662,0.0004211995,0.001853212,0.00170913,0.001374928,0.003823948],"category_scores_gemma":[0.02582374,0.0006245623,0.001032336,0.001083435,0.001895387,0.003605948,0.002965102,0.003207796,0.00080235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007631432,"about_ca_system_score_gemma":0.000886501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006894637,"about_ca_topic_score_gemma":0.0006696797,"domain_scores_codex":[0.9980849,0.001124468,0.00008385373,0.0002026691,0.0004319198,0.0000721544],"domain_scores_gemma":[0.9884288,0.009699109,0.0005889264,0.0005499225,0.0005300461,0.0002033023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009201518,0.00007165869,0.0009553079,0.0002018161,0.00006117228,0.0002649784,0.0001595312,0.3937885,0.003579139,0.5144468,0.001949505,0.08442968],"study_design_scores_gemma":[0.000006351155,0.00001612063,0.000102964,0.00001821101,0.000005435244,0.00005689781,0.000008005484,0.8969948,0.0005811987,0.1014177,0.0007786111,0.00001371052],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001447249,0.000142692,0.997748,0.00009211076,0.00001347222,0.000009909726,0.00001585152,0.00004858838,0.0004822274],"genre_scores_gemma":[0.3148235,0.001611135,0.6744912,0.0003823198,0.0004208064,0.0003475943,0.0004151913,0.0004364531,0.007071741],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004635142,"threshold_uncertainty_score":0.02451324,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2771866761","doi":"10.4236/ojs.2017.76068","title":"Atmospheric Observation under Sampling Problem: The Impact of Unresolved Micro-Scale Boundary Layer Eddies on Climate Trends","year":2017,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Environmental science; Climatology; Atmosphere (unit); Eddy; Scale (ratio); Atmospheric sciences; Climate change; Climate model; Amplitude; Boundary layer; Meteorology; Geology; Geography; Turbulence; Physics","authors":[{"name":"Atoossa Bakhshaii","is_ca":true},{"name":"Edward A. Johnson","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1140384946318144,"gpt":0.3486710237133095,"spread":0.2346325290814952,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02164314,0.0004581338,0.0009129368,0.0005661622,0.001247898,0.00154635,0.001499851,0.001987453,0.002582226],"category_scores_gemma":[0.1076609,0.0004767619,0.0009126803,0.001353913,0.001728906,0.002839139,0.001595398,0.0018411,0.0001923658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009406144,"about_ca_system_score_gemma":0.001236622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01594588,"about_ca_topic_score_gemma":0.009143061,"domain_scores_codex":[0.9940372,0.002870882,0.0003343326,0.001691023,0.0006948718,0.0003717352],"domain_scores_gemma":[0.8866903,0.09092224,0.01014898,0.008252307,0.002782415,0.001203772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001326041,0.0002434555,0.5870783,0.0008262892,0.001753037,0.002299162,0.001175207,0.1729612,0.004473506,0.08398928,0.01404907,0.1298255],"study_design_scores_gemma":[0.0003183609,0.0003410943,0.218507,0.0001911679,0.0008092682,0.001070981,0.0006748852,0.7021055,0.004554327,0.06056353,0.01073889,0.0001249384],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5488865,0.006249266,0.413938,0.01439452,0.001850467,0.0003015141,0.00343066,0.0007804691,0.01016855],"genre_scores_gemma":[0.9844542,0.0009850254,0.01064839,0.0008342162,0.0007332287,0.00006799509,0.0007712811,0.00009117797,0.001414468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02164314,"threshold_uncertainty_score":0.1144612,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2025324018","doi":"10.4236/ojs.2014.43018","title":"Theoretical Properties of Composite Likelihoods","year":2014,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Mechanics and Entropy","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Quasi-maximum likelihood; Inference; Principle of maximum entropy; Composite number; Mathematics; Kullback–Leibler divergence; Entropy (arrow of time); Maximum likelihood; Applied mathematics; Projection (relational algebra); Statistical physics; Computer science; Algorithm; Statistics; Likelihood function; Artificial intelligence; Physics","authors":[{"name":"Xiaogang Wang","is_ca":true},{"name":"Yuehua Wu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01361788808502547,"gpt":0.2593433638503005,"spread":0.2457254757652751,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0124668,0.001007047,0.001287093,0.004298559,0.001183805,0.004721158,0.002984169,0.002203738,0.005919899],"category_scores_gemma":[0.05733133,0.0008412339,0.001618581,0.002801538,0.00546174,0.00839797,0.004268968,0.004212859,0.00105503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001898359,"about_ca_system_score_gemma":0.001641355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006821758,"about_ca_topic_score_gemma":0.0004605422,"domain_scores_codex":[0.9944751,0.002184359,0.0003042597,0.000948659,0.00178684,0.0003009003],"domain_scores_gemma":[0.9543449,0.03650727,0.002671318,0.002578313,0.003095972,0.000802176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000200328,0.00001237898,0.000646839,0.00008160542,0.00001981879,0.00006859732,0.00009505628,0.02991756,0.0003905539,0.9589544,0.0005938775,0.009199321],"study_design_scores_gemma":[0.000006290152,0.00001974374,0.0002861341,0.00003106686,0.000008585377,0.0001057687,0.00002053943,0.1522867,0.000282749,0.8461812,0.0007512981,0.0000198038],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01114702,0.0003953978,0.9815844,0.0005433293,0.00004036081,0.00003519591,0.0002072986,0.0001279225,0.005919013],"genre_scores_gemma":[0.5948247,0.0025472,0.3908633,0.0006911133,0.0007345848,0.0007460782,0.001245143,0.0004355676,0.00791241],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0124668,"threshold_uncertainty_score":0.06593156,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2791604340","doi":"10.4236/ojs.2018.81010","title":"A Chi-Square Approximation for the &amp;lt;i&amp;gt;F&amp;lt;/i&amp;gt; Distribution","year":2018,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Mathematics; Statistics; Distribution (mathematics); F-distribution; Square (algebra); Chi-square test; Statistic; Normal distribution; Cumulative distribution function; Combinatorics; Mathematical analysis; Probability distribution; Probability density function","authors":[{"name":"Lai Jiang","is_ca":false},{"name":"Augustine Wong","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1501519387144394,"gpt":0.4154162127582547,"spread":0.2652642740438153,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01311178,0.001696234,0.001589764,0.003256741,0.001138376,0.002085377,0.003774278,0.002845198,0.0175297],"category_scores_gemma":[0.08366045,0.0006412776,0.001504152,0.003871022,0.003523917,0.004112252,0.00190841,0.005613671,0.01104531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001309919,"about_ca_system_score_gemma":0.002175839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004180878,"about_ca_topic_score_gemma":0.003007866,"domain_scores_codex":[0.9909269,0.003713015,0.0003839881,0.001602805,0.002899249,0.0004741308],"domain_scores_gemma":[0.9547998,0.03287425,0.001725298,0.004828106,0.005308405,0.0004641371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004185395,0.0002548111,0.01004679,0.0009881611,0.0002672042,0.001575893,0.001467544,0.07476992,0.01293834,0.4072825,0.03599971,0.4539905],"study_design_scores_gemma":[0.00009155482,0.0003517999,0.006505436,0.0003158074,0.0001063921,0.002774366,0.0004387115,0.6778409,0.00949968,0.2550317,0.04683367,0.000209947],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002051298,0.0002647609,0.9953288,0.0001807288,0.0001246346,0.00006503626,0.0001365337,0.0005641373,0.001284039],"genre_scores_gemma":[0.1584664,0.00126335,0.8237025,0.0006790165,0.0006324411,0.001347569,0.00139263,0.001090024,0.01142597],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0175297,"threshold_uncertainty_score":0.06934255,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3135631171","doi":"10.4236/ojs.2021.112014","title":"Predictors of the Aggregate of COVID-19 Cases and Its Case-Fatality: A Global Investigation Involving 120 Countries","year":2021,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"COVID-19 Clinical Research Studies","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Case fatality rate; Pandemic; Medicine; Negative binomial distribution; Coronavirus disease 2019 (COVID-19); Demography; Population; Regression analysis; Disease; Environmental health; Statistics; Infectious disease (medical specialty); Internal medicine; Mathematics","authors":[{"name":"Sarah Algahtani","is_ca":false},{"name":"Mohamed M. Shoukri","is_ca":true},{"name":"Maha Al-Eid","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1128099696541836,"gpt":0.4420111225663732,"spread":0.3292011529121897,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002220586,0.0005986856,0.0007887381,0.002467444,0.0003342499,0.0009668064,0.000497835,0.0004475039,0.001215206],"category_scores_gemma":[0.004710972,0.0003651899,0.001585412,0.00399746,0.0005301698,0.0009145631,0.001130241,0.0008054947,0.0002889771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004068517,"about_ca_system_score_gemma":0.0003788168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006326403,"about_ca_topic_score_gemma":0.003144381,"domain_scores_codex":[0.9987011,0.0004645786,0.000170672,0.0003542999,0.0001625138,0.0001468183],"domain_scores_gemma":[0.9955623,0.001317939,0.002058801,0.0003449895,0.0004333215,0.0002826793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007427928,0.00001259185,0.9965256,0.00005316409,0.000221806,0.00007699023,0.0001067685,0.0003506238,0.00004006275,0.00004489127,0.0002693497,0.00222383],"study_design_scores_gemma":[0.00000893016,0.00009382423,0.9958445,0.00006672037,0.0001760339,0.0004983726,0.0008148023,0.001365355,0.0000763354,0.0001060751,0.0009362634,0.00001262941],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917961,0.003045966,0.0005161777,0.0001874439,0.00001474648,0.00002177168,0.003678317,0.00001816144,0.0007212057],"genre_scores_gemma":[0.9955746,0.001076518,0.0002193459,0.00003087601,0.00002128065,0.00001953393,0.002972724,0.000007987158,0.00007719131],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006326403,"threshold_uncertainty_score":0.01257914,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4383739011","doi":"10.4236/ojs.2023.134021","title":"Modeling Cyber Loss Severity Using a Spliced Regression Distribution with Mixture Components","year":2023,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Burnaby Hospital","funders":"","keywords":"Expectation–maximization algorithm; Covariate; Mixture model; Range (aeronautics); Computer science; Aggregate (composite); Generalized linear model; Statistics; Econometrics; Heavy-tailed distribution; Data mining; Mathematics; Probability distribution; Maximum likelihood; Engineering","authors":[{"name":"Meng Sun","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05786021716252401,"gpt":0.3354950161118946,"spread":0.2776347989493706,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005819841,0.001499204,0.001458221,0.002318182,0.0005641604,0.002201944,0.003540612,0.002229048,0.00312032],"category_scores_gemma":[0.01339003,0.001057283,0.002691845,0.001989421,0.001506184,0.002944201,0.002185931,0.003072228,0.001054964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001248165,"about_ca_system_score_gemma":0.0009666217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01139767,"about_ca_topic_score_gemma":0.007973947,"domain_scores_codex":[0.9971948,0.001221414,0.0001456985,0.0007741679,0.0004013328,0.0002625129],"domain_scores_gemma":[0.9928301,0.004601038,0.0009268593,0.0006607719,0.0007973175,0.0001838931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002876717,0.0002392502,0.01300059,0.00007406835,0.000205715,0.0001898663,0.0003222478,0.8983615,0.001526537,0.04195857,0.001388287,0.04244577],"study_design_scores_gemma":[0.000008507831,0.00002835865,0.0009943817,0.000007143892,0.00002069467,0.00002685022,0.00002148688,0.9920797,0.000160973,0.006400303,0.0002376711,0.00001397442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08189467,0.0002050786,0.9153082,0.000480398,0.0000551789,0.0001376191,0.0004118546,0.0004974956,0.001009413],"genre_scores_gemma":[0.8560924,0.0005141444,0.133228,0.0002153437,0.0001200585,0.0004250323,0.001393865,0.000158761,0.007852428],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01139767,"threshold_uncertainty_score":0.03077865,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2609350886","doi":"10.4236/ojs.2017.72019","title":"Estimation of Attributable Risk from Clustered Binary Data: The Case of Cross-Sectional and Cohort Studies","year":2017,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Robarts Clinical Trials; Western University","funders":"","keywords":"Statistics; Confidence interval; Mathematics; Monte Carlo method; Wald test; Inference; Interval estimation; Coverage probability; Cluster (spacecraft); Correlation; Variance (accounting); Aggregate (composite); Econometrics; Statistical hypothesis testing; Binary data; Statistical inference; Binary number; Computer science","authors":[{"name":"Mohamed M. Shoukri","is_ca":false},{"name":"Allan Donner","is_ca":true},{"name":"Futwan Al‐Mohanna","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2740426777950981,"gpt":0.5118138189660502,"spread":0.237771141170952,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1251897,0.001283647,0.003648137,0.004563124,0.001095935,0.003516235,0.004997877,0.005045251,0.002421693],"category_scores_gemma":[0.3954268,0.00117595,0.002510461,0.006230216,0.00483142,0.005000922,0.004217179,0.004301785,0.0003437636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001383413,"about_ca_system_score_gemma":0.00192451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003753494,"about_ca_topic_score_gemma":0.001797996,"domain_scores_codex":[0.8766248,0.1047227,0.003444553,0.008087536,0.006525514,0.0005949203],"domain_scores_gemma":[0.5955327,0.3501807,0.01807554,0.03185159,0.003723282,0.000636149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005032978,0.0001890238,0.06515299,0.003930598,0.007022173,0.001651438,0.002120186,0.06328674,0.0008841614,0.6880222,0.002990349,0.1642468],"study_design_scores_gemma":[0.0001163391,0.0002602772,0.01295867,0.0008668359,0.001055419,0.000777551,0.0004085237,0.1044561,0.0008798557,0.8703772,0.007737345,0.0001057859],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01337485,0.004102302,0.9794322,0.001281225,0.0002603299,0.0003015546,0.0002956272,0.00008314203,0.0008687269],"genre_scores_gemma":[0.3287622,0.006488891,0.6580909,0.001073721,0.0008628626,0.002577438,0.0006633031,0.0001082751,0.001372496],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1251897,"threshold_uncertainty_score":0.6620742,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4225609744","doi":"10.4236/ojs.2022.122016","title":"Quasi-Negative Binomial: Properties, Parametric Estimation, Regression Model and Application to RNA-SEQ Data","year":2022,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Overdispersion; Count data; Negative binomial distribution; Quasi-likelihood; Akaike information criterion; Beta-binomial distribution; Mathematics; Statistics; Binomial distribution; Multinomial distribution; Poisson distribution; Negative multinomial distribution; Goodness of fit","authors":[{"name":"Mohamed M. Shoukri","is_ca":true},{"name":"Maha Al-Eid","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07842162581472943,"gpt":0.3468887030059208,"spread":0.2684670771911913,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01418717,0.0007467904,0.001242109,0.001734633,0.0007225922,0.001794362,0.002869227,0.00170118,0.003862621],"category_scores_gemma":[0.03781099,0.0006391254,0.001545809,0.002592774,0.002050916,0.002343559,0.001346546,0.002703887,0.001100199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001442986,"about_ca_system_score_gemma":0.001626503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005523526,"about_ca_topic_score_gemma":0.003850087,"domain_scores_codex":[0.9961534,0.00238166,0.0001283473,0.0005914267,0.0006011556,0.0001440028],"domain_scores_gemma":[0.9710177,0.02335973,0.002588789,0.001137919,0.00159694,0.0002989404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002583819,0.0001534708,0.02150931,0.0008543516,0.0002789528,0.0008653487,0.0008112764,0.5484853,0.008424275,0.2980092,0.006591094,0.1137589],"study_design_scores_gemma":[0.00001099019,0.00003907648,0.001735527,0.00004244678,0.0000216351,0.0003656539,0.0000450689,0.9273327,0.000503245,0.06742288,0.002446996,0.00003383207],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00910528,0.000407284,0.9891662,0.0002766243,0.00003261612,0.00004979976,0.000185368,0.0002441306,0.0005326043],"genre_scores_gemma":[0.3748725,0.002276653,0.6132215,0.0005410026,0.0002647322,0.001069777,0.001917311,0.0005210816,0.005315437],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01418717,"threshold_uncertainty_score":0.07502985,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2898865804","doi":"10.4236/ojs.2018.85056","title":"Asymptotic Normality Distribution of Simulated Minimum Hellinger Distance Estimators for Continuous Models","year":2018,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval; Ontario Universities’ Application Centre","funders":"","keywords":"Estimator; Hellinger distance; Mathematics; Asymptotic distribution; Applied mathematics; Parametric statistics; Fisher information; Delta method; Statistics; Quantile","authors":[{"name":"Andrew Luong","is_ca":true},{"name":"Claire Bilodeau","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05800429756137201,"gpt":0.2868693424299021,"spread":0.2288650448685301,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01369705,0.0005533482,0.001190421,0.001607084,0.0005639808,0.001741872,0.00182031,0.001519715,0.002502401],"category_scores_gemma":[0.1141924,0.0005872247,0.0008851582,0.0007817675,0.003778835,0.005151953,0.002465695,0.00250198,0.0005015607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001806324,"about_ca_system_score_gemma":0.001408908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001041962,"about_ca_topic_score_gemma":0.0006615792,"domain_scores_codex":[0.994984,0.002781644,0.0002488134,0.0007400434,0.00099103,0.0002544573],"domain_scores_gemma":[0.9154312,0.06874143,0.003761069,0.007324014,0.004004901,0.0007373556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002027202,0.0001032261,0.00949042,0.0001704886,0.0001214637,0.0001732179,0.0004597161,0.3687219,0.002319,0.588343,0.001792707,0.02810213],"study_design_scores_gemma":[0.00002204845,0.00005685816,0.001524542,0.00004899731,0.00001187439,0.000117921,0.00006276397,0.7675176,0.001353704,0.2284355,0.000808558,0.00003969736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07237598,0.0003454641,0.9236364,0.0006014031,0.0000304984,0.00005727456,0.0001776814,0.0002564885,0.002518818],"genre_scores_gemma":[0.8907559,0.0005128385,0.1050867,0.000214138,0.00009914512,0.000337953,0.0008693496,0.0001491587,0.00197488],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01369705,"threshold_uncertainty_score":0.07243776,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4312577525","doi":"10.4236/ojs.2022.125043","title":"Statistical Analysis of Small Holder Farmer Financial Exclusion: Case Study of Migori County, Kenya","year":2022,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Microfinance and Financial Inclusion","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"International Development Research Centre; Styrelsen för Internationellt Utvecklingssamarbete","keywords":"Developing country; Scale (ratio); Business; Agricultural economics; Agricultural science; Economics; Finance; Economic growth; Geography","authors":[{"name":"Susan A. Okeyo","is_ca":false},{"name":"Galcano C. Mulaku","is_ca":false},{"name":"Collins M. Mwange","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06106595504378557,"gpt":0.2885441527564038,"spread":0.2274781977126182,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002431705,0.0001914222,0.0003471922,0.001442029,0.001719933,0.0006544174,0.0005202881,0.0004545032,0.002339307],"category_scores_gemma":[0.009023583,0.0001149259,0.0002975661,0.002561084,0.0008708104,0.000549074,0.0008136484,0.0006347969,0.0001322522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00118121,"about_ca_system_score_gemma":0.001186953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05220207,"about_ca_topic_score_gemma":0.09073184,"domain_scores_codex":[0.9981812,0.001094365,0.0001021967,0.0001663877,0.0001798416,0.0002760056],"domain_scores_gemma":[0.9906235,0.006112385,0.001606272,0.0002803894,0.0009640928,0.0004132911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002790185,0.0003676511,0.9580775,0.0002069546,0.0001208059,0.00835428,0.01062511,0.001125096,0.000652414,0.001773414,0.001602111,0.01681557],"study_design_scores_gemma":[0.0000169122,0.0004062254,0.9283455,0.0001041553,0.0001116946,0.001579923,0.05830514,0.006105154,0.0004936566,0.0006183393,0.003885866,0.00002742587],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982142,0.0001185451,0.0003983475,0.0001888293,0.000003223187,0.00004437277,0.0001746046,0.000002189551,0.0008557077],"genre_scores_gemma":[0.9986333,0.0001080783,0.0005433165,0.00002710475,0.000005193551,0.00003319962,0.000162874,0.000001953113,0.0004848222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05220207,"threshold_uncertainty_score":0.1037964,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2077456109","doi":"10.4236/ojs.2012.25070","title":"Data Fusion Using Empirical Likelihood","year":2012,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Empirical likelihood; Estimator; Inference; Statistics; Maximum likelihood; Estimating equations; Mathematics; Computer science; Parametric statistics; Statistical inference; Confidence interval; Econometrics; Artificial intelligence","authors":[{"name":"Hsiao‐Hsuan Wang","is_ca":true},{"name":"Yuehua Wu","is_ca":true},{"name":"Yuejiao Fu","is_ca":true},{"name":"Xiaogang Wang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.5438412272793877,"gpt":0.5668018232046595,"spread":0.02296059592527189,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008818028,0.00139412,0.003314931,0.003771826,0.0007915624,0.00327246,0.003196387,0.002569096,0.002212061],"category_scores_gemma":[0.03044107,0.001139829,0.00266895,0.004308581,0.001597159,0.005584621,0.006931013,0.002625089,0.001545711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008801831,"about_ca_system_score_gemma":0.001385136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009734607,"about_ca_topic_score_gemma":0.0006288454,"domain_scores_codex":[0.9917825,0.003470852,0.0006708774,0.001490072,0.002299468,0.0002862132],"domain_scores_gemma":[0.990522,0.004457861,0.0009954371,0.002264512,0.001608622,0.0001516612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004144414,0.0001695603,0.002109553,0.0006450897,0.0007710999,0.000385613,0.0005283909,0.2373815,0.01404569,0.09889829,0.003100099,0.6415507],"study_design_scores_gemma":[0.00004626479,0.0001048282,0.0006384338,0.0000584534,0.00008928564,0.0002014312,0.00005687173,0.9253001,0.006167472,0.06184316,0.0054006,0.00009313662],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001104788,0.0001945211,0.9981076,0.00007038842,0.00002205124,0.00002211101,0.00002486638,0.0001708169,0.0002828336],"genre_scores_gemma":[0.1807946,0.0008761368,0.8150952,0.0003314729,0.0002268495,0.0003207825,0.0005542683,0.0001894255,0.001611307],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008818028,"threshold_uncertainty_score":0.04663473,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4380980112","doi":"10.4236/ojs.2023.133015","title":"Empirical Bayesian Approach to Testing Homogeneity of Several Means of Inflated Poisson Distributions (IPD)","year":2023,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Mathematics; Prior probability; Conjugate prior; Poisson distribution; Statistics; Homogeneity (statistics); Bayesian linear regression; Applied mathematics; Bayesian probability; Gamma distribution; Likelihood function; Bayesian inference; Estimation theory","authors":[{"name":"Mohamed M. Shoukri","is_ca":true},{"name":"Maha Al-Eid","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1818348590447256,"gpt":0.4296123084514148,"spread":0.2477774494066892,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03207368,0.001046756,0.002025914,0.00348131,0.001179616,0.003081159,0.003928221,0.002568244,0.005528085],"category_scores_gemma":[0.1087778,0.0009525192,0.002233593,0.002510989,0.003720072,0.003613224,0.003499639,0.004093853,0.0006786761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002281244,"about_ca_system_score_gemma":0.002754373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003492155,"about_ca_topic_score_gemma":0.002115264,"domain_scores_codex":[0.9689201,0.02104751,0.001306008,0.004621745,0.003505727,0.0005989412],"domain_scores_gemma":[0.9275669,0.06024767,0.00485001,0.003166765,0.00361858,0.0005501073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005158739,0.0003362352,0.02438801,0.001010506,0.001084916,0.0007642557,0.001747963,0.1708209,0.00588414,0.5736644,0.004891752,0.2148909],"study_design_scores_gemma":[0.0001090395,0.0002014119,0.006395228,0.0002466858,0.0001700784,0.0006467894,0.000259884,0.4918416,0.003001199,0.4898223,0.007171635,0.000134128],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00698092,0.0001829509,0.9911557,0.0002382629,0.00003075896,0.0001304428,0.0001575307,0.0001827299,0.000940684],"genre_scores_gemma":[0.2137256,0.0004243994,0.7810366,0.0005202286,0.0001924163,0.001435001,0.0007899127,0.0001963619,0.001679653],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03207368,"threshold_uncertainty_score":0.1696239,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2773922713","doi":"10.4236/ojs.2017.76064","title":"A Neighborhood Analysis of Underage Tobacco Sales within the Serving Area of a Canadian Public Health Unit","year":2017,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Smoking Behavior and Cessation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Centers for Disease Control and Prevention; Imperial College London; Cancer Care Ontario","keywords":"Windsor; Unit (ring theory); Environmental health; Geography; Tobacco control; Enforcement; Business; Public health; Cluster (spacecraft); Relative risk; Statistics; Medicine; Environmental science; Mathematics; Computer science; Political science","authors":[{"name":"Saber Fallahpour","is_ca":false},{"name":"Tanya Navaneelan","is_ca":false},{"name":"Kristy McBeth","is_ca":false},{"name":"Prithwish De","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1855071922532952,"gpt":0.3793564222930715,"spread":0.1938492300397763,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005801744,0.0002371374,0.0003839707,0.00173705,0.001594037,0.0008639967,0.0007871981,0.0002296194,0.001718247],"category_scores_gemma":[0.002643398,0.0001997339,0.0006972266,0.002612157,0.0003824334,0.0002704508,0.0009463765,0.0002551594,0.0001160893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006149371,"about_ca_system_score_gemma":0.007454019,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9720675,"about_ca_topic_score_gemma":0.98245,"domain_scores_codex":[0.9992155,0.0001077209,0.00004669082,0.0002122221,0.0002177036,0.000200154],"domain_scores_gemma":[0.9984902,0.0001998898,0.0003440704,0.0001356374,0.0005438155,0.0002863292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006753652,0.00001476526,0.995101,0.00001492501,0.00009435156,0.00007585223,0.0006567604,0.0003202198,0.000321429,0.0001330877,0.0002669239,0.002933288],"study_design_scores_gemma":[0.000001907582,0.00002823282,0.9971334,0.00000740395,0.00002768411,0.00003231838,0.001159108,0.001145672,0.0000400899,0.0000187426,0.0003999676,0.000005488612],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980274,0.00009369546,0.0002141608,0.00002781414,0.000002095819,0.00001853298,0.0009729904,0.000006113144,0.0006372054],"genre_scores_gemma":[0.99845,0.00005397952,0.0003211717,0.000006190875,9.498488e-7,0.00001025566,0.0007490198,0.000003332994,0.0004050831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02793252,"threshold_uncertainty_score":0.05619401,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1497365461","doi":"10.4236/ojs.2017.72022","title":"Testing the Adding up Condition in Demand Systems","year":2017,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Economics of Agriculture and Food Markets","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Almost ideal demand system; Commodity; Affine transformation; Sample (material); Econometrics; Computer science; On demand; Quadratic equation; Confidence interval; Statistics; Mathematics; Economics; Microeconomics; Production (economics); Finance","authors":[{"name":"Quirino Paris","is_ca":false},{"name":"Francesco Caracciolo","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08185088547037728,"gpt":0.2755303591129556,"spread":0.1936794736425784,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05939013,0.001284456,0.003047945,0.003619021,0.002651677,0.005249572,0.003911274,0.004189493,0.0309356],"category_scores_gemma":[0.3511484,0.001012989,0.003936077,0.003780352,0.0101084,0.01228756,0.005864835,0.005307257,0.002075309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001587003,"about_ca_system_score_gemma":0.003513977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00253918,"about_ca_topic_score_gemma":0.0008866058,"domain_scores_codex":[0.920212,0.04228426,0.007963442,0.01267915,0.01149142,0.00536979],"domain_scores_gemma":[0.2615182,0.6680535,0.02692218,0.02699951,0.01181328,0.004693295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.006818219,0.002692493,0.4628031,0.001296828,0.002004875,0.003330813,0.005711166,0.05730234,0.009364324,0.3281245,0.005987508,0.1145638],"study_design_scores_gemma":[0.001682959,0.008616818,0.1927112,0.0004020458,0.0007750641,0.001778321,0.009754562,0.4483424,0.01774647,0.3076215,0.01005491,0.000513817],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8731664,0.000133963,0.1079591,0.001906219,0.0001680971,0.0005637005,0.002068678,0.0004199788,0.01361366],"genre_scores_gemma":[0.9839486,0.00005084872,0.01251485,0.0002867723,0.0001580816,0.0003583263,0.00173099,0.00004841079,0.000903067],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05939013,"threshold_uncertainty_score":0.3140888,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2911568234","doi":"10.4236/ojs.2019.91006","title":"Analysis of Hospital Mortality Data: The Role of DRG’s","year":2019,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Gee; Generalized estimating equation; Medicine; Logistic regression; Generalized linear model; Statistics; Cluster analysis; Statistical model; Linear regression; Regression analysis; Nuisance parameter; Econometrics; Mathematics; Internal medicine","authors":[{"name":"Mohamed M. Shoukri","is_ca":true},{"name":"Sara N. Algahtani","is_ca":false},{"name":"Abdelmoneim Eldali","is_ca":false},{"name":"Manal Rashed Almarzouqi","is_ca":false},{"name":"Saleh M. Al-Ageel","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03274084228201806,"gpt":0.3591191087906706,"spread":0.3263782665086525,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03071847,0.0007199775,0.0009977501,0.002616685,0.0003463097,0.001446557,0.001147271,0.0004564871,0.001793729],"category_scores_gemma":[0.08447649,0.0001858003,0.001575665,0.004701792,0.001093232,0.001084461,0.00112309,0.001421215,0.000360945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00142143,"about_ca_system_score_gemma":0.002053326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002403965,"about_ca_topic_score_gemma":0.002345223,"domain_scores_codex":[0.9554357,0.03540871,0.002360192,0.002524093,0.003836534,0.0004347967],"domain_scores_gemma":[0.8281479,0.1451377,0.01281634,0.008552072,0.004688513,0.0006575725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009548596,0.0001906923,0.7172999,0.001658246,0.002762252,0.0002658943,0.0008234607,0.02059105,0.00191718,0.01154711,0.004299887,0.2376895],"study_design_scores_gemma":[0.000113796,0.001448491,0.7347652,0.001204164,0.001076305,0.001569573,0.001416295,0.176869,0.007606098,0.05564833,0.0181209,0.0001619437],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5321395,0.006627037,0.4419435,0.004059726,0.0003316972,0.0005263126,0.008584455,0.0007355296,0.005052192],"genre_scores_gemma":[0.9075727,0.0009747297,0.08811616,0.0003119449,0.0001131452,0.0002421754,0.002153137,0.0001341397,0.0003818517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03071847,"threshold_uncertainty_score":0.1624568,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4312720532","doi":"10.4236/ojs.2022.125041","title":"Extreme Values Approach in Food Risk Modeling","year":2022,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Health Canada","keywords":"Statistics; Random variable; Cumulative distribution function; Mixture distribution; Probabilistic logic; Mathematics; Gaussian; Econometrics; Computer science; Applied mathematics; Probability density function","authors":[{"name":"Komla Elom Adedje","is_ca":false},{"name":"Diakarya Barro","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04367105442217675,"gpt":0.2620013291254117,"spread":0.218330274703235,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004090097,0.001258666,0.001701695,0.001634807,0.0005736792,0.002010378,0.002269324,0.002085318,0.002383612],"category_scores_gemma":[0.009157808,0.0008696537,0.001586035,0.001531171,0.001661722,0.001824002,0.001837587,0.002745963,0.0003647425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00137094,"about_ca_system_score_gemma":0.001076997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006268794,"about_ca_topic_score_gemma":0.003698974,"domain_scores_codex":[0.9980891,0.001238037,0.00006886673,0.0002347464,0.0002430315,0.0001261332],"domain_scores_gemma":[0.9945827,0.004548935,0.0003551433,0.0001291615,0.0002529699,0.0001310352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001236613,0.00001867435,0.0006104701,0.00003815489,0.00008592878,0.00008501836,0.00004049419,0.9153138,0.00009402161,0.07646997,0.0005870016,0.006644167],"study_design_scores_gemma":[0.000004680695,0.0000124018,0.0001188343,0.00001149323,0.00001049007,0.00001927927,0.00001554481,0.8676065,0.00003546334,0.1313013,0.0008519361,0.00001213353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005773407,0.0008808316,0.9902319,0.0006148363,0.00006622588,0.00002705754,0.0001276334,0.00008068312,0.0021974],"genre_scores_gemma":[0.6896273,0.004043397,0.2905246,0.0006164538,0.0007813537,0.000573024,0.0007041747,0.0002381439,0.01289164],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006268794,"threshold_uncertainty_score":0.02163076,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2013698137","doi":"10.4236/ojs.2011.12013","title":"Empirical Analysis of Impact of Conversion ofConvertible Bonds on Corporate Performance of Different Industries in China","year":2011,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"Convertible bond; Wilcoxon signed-rank test; China; Convertible; Business; Empirical research; Bond; Econometrics; Accounting; Financial economics; Economics; Mathematics; Statistics; Finance; Engineering; Geography","authors":[{"name":"Hua Ding","is_ca":false},{"name":"Xuewen Lu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07866145090431585,"gpt":0.2826275167291125,"spread":0.2039660658247966,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001516772,0.0002820615,0.000265866,0.002048607,0.000306971,0.0009013846,0.0003501192,0.0002689009,0.0007849321],"category_scores_gemma":[0.00485862,0.0001239191,0.000491012,0.002718625,0.0004201526,0.0004835277,0.0005143248,0.0003979653,0.0001114089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009979926,"about_ca_system_score_gemma":0.0008140784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02177337,"about_ca_topic_score_gemma":0.02260866,"domain_scores_codex":[0.9988891,0.0002100113,0.0001351352,0.0001951858,0.0003849053,0.0001856715],"domain_scores_gemma":[0.9926416,0.001660676,0.003106134,0.0004474849,0.001337072,0.0008070284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002931147,0.00002145829,0.9956928,0.00000792345,0.00005515238,0.0001030954,0.0001083091,0.0003951618,0.000201928,0.00006063066,0.00006210838,0.003262215],"study_design_scores_gemma":[8.515673e-7,0.0000152546,0.9993227,0.000001296424,0.000008822863,0.00001442838,0.00006546571,0.0004456527,0.00006209705,0.00001089817,0.00005098572,0.000001594136],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994308,0.00008986443,0.00004083755,0.00001997771,0.000001109272,0.000003040779,0.0001021033,0.000001977614,0.0003101924],"genre_scores_gemma":[0.9996531,0.00004073227,0.00001896971,0.000002703373,0.000002891353,0.000001314955,0.0001993201,4.954e-7,0.00008039411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02177337,"threshold_uncertainty_score":0.04329324,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3121383538","doi":"10.4236/ojs.2021.111010","title":"Uncovering and Displaying the Coherent Groups of Rank Data by Exploratory Riffle Shuffling","year":2021,"lang":"en","type":"preprint","venue":"Open Journal of Statistics","topic":"Sensory Analysis and Statistical Methods","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Shuffling; Riffle; Rank (graph theory); Set (abstract data type); Contingency table; Combinatorics; Mathematics; Computer science; Statistics","authors":[{"name":"Vartan Choulakian","is_ca":true},{"name":"Jacques Allard","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.127473884003913,"gpt":0.3421310414580429,"spread":0.2146571574541299,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004602412,0.0005441676,0.0008933239,0.004572826,0.0009277862,0.001838132,0.0008129668,0.0008594741,0.002510955],"category_scores_gemma":[0.0215433,0.0003630312,0.0009381517,0.003537678,0.001664768,0.001986675,0.002045674,0.001121032,0.000601815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009403236,"about_ca_system_score_gemma":0.0008323217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002286103,"about_ca_topic_score_gemma":0.002637318,"domain_scores_codex":[0.9964818,0.002049827,0.0001584839,0.0005319408,0.000520073,0.0002579122],"domain_scores_gemma":[0.9808351,0.01106541,0.002201034,0.004202371,0.001182662,0.0005134151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002675317,0.0006732089,0.2150998,0.0007214182,0.000522875,0.001626271,0.009947794,0.09628099,0.02661228,0.1949984,0.01340349,0.4374382],"study_design_scores_gemma":[0.0001631584,0.0008003601,0.09100951,0.0001313098,0.00008992058,0.0009936348,0.004130589,0.5671432,0.0132229,0.3079169,0.01415032,0.0002482458],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5907061,0.0004232086,0.3991083,0.0006148597,0.00002741808,0.0002837195,0.003404367,0.0009324131,0.004499725],"genre_scores_gemma":[0.8941864,0.00009922918,0.1016976,0.00007645194,0.00003284296,0.0002170956,0.002870207,0.00006258162,0.0007574197],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.004602412,"threshold_uncertainty_score":0.02434021,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4231925469","doi":"10.4236/ojs.2014.4811","title":"Interval Estimation for the Stress-Strength Reliability with Bivariate Normal Variables","year":2014,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University; Simon Fraser University","funders":"","keywords":"Bivariate analysis; Reliability (semiconductor); Mathematics; Statistics; Confidence interval; Covariance matrix; Multivariate normal distribution; Coverage probability; Multivariate statistics; Power (physics)","authors":[{"name":"Pierre Nguimkeu","is_ca":false},{"name":"Marie Rekkas","is_ca":true},{"name":"Augustine Wong","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04785396032131278,"gpt":0.3611498025271931,"spread":0.3132958422058803,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01105035,0.001276131,0.001632656,0.00422272,0.0004453453,0.001233546,0.002649332,0.001251999,0.001825486],"category_scores_gemma":[0.08408,0.000474823,0.001289802,0.002824731,0.001108009,0.002084889,0.001987397,0.002505653,0.000735296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004155152,"about_ca_system_score_gemma":0.0008194623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001488397,"about_ca_topic_score_gemma":0.0006485049,"domain_scores_codex":[0.9926077,0.003899455,0.0004818849,0.001034039,0.001755786,0.0002212777],"domain_scores_gemma":[0.92125,0.06406116,0.005587453,0.004311857,0.004322669,0.0004668028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004596855,0.0001560213,0.01850423,0.0008076674,0.000444076,0.0003899533,0.0006289685,0.4173069,0.009082076,0.08415751,0.002464506,0.4655984],"study_design_scores_gemma":[0.00002765511,0.0001547944,0.003323349,0.00008384255,0.00006661861,0.0003241406,0.00005111271,0.9554151,0.003434058,0.03528329,0.001759222,0.00007679127],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002606602,0.0001925939,0.9968554,0.00001642536,0.00001081236,0.00001490446,0.00003958683,0.0001338987,0.0001298059],"genre_scores_gemma":[0.2228902,0.001035557,0.7739997,0.00006786771,0.0002359454,0.000375785,0.0007896248,0.0001321033,0.0004732784],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01105035,"threshold_uncertainty_score":0.05844051,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2893237262","doi":"10.4236/ojs.2018.85055","title":"An Examination of Male and Female Monthly Employment Rates over Time in Canada and the United States Using Hidden Markov Probability Models","year":2018,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Hidden Markov model; Multivariate statistics; Markov chain; Markov model; Demography; Econometrics; Statistics; Multivariate analysis; Demographic economics; Geography; Economics; Mathematics; Computer science; Sociology; Artificial intelligence","authors":[{"name":"W. H. Laverty","is_ca":true},{"name":"I. W. Kelly","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03434236485397418,"gpt":0.3106313745297916,"spread":0.2762890096758174,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001650104,0.0001786433,0.0002615931,0.001872887,0.00068419,0.0009742898,0.0005536228,0.0003031395,0.00156025],"category_scores_gemma":[0.00857918,0.0001783925,0.0004573231,0.003671713,0.0003063222,0.0004371235,0.0004221769,0.000508055,0.0001657164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003280185,"about_ca_system_score_gemma":0.004563934,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9136642,"about_ca_topic_score_gemma":0.9287052,"domain_scores_codex":[0.9995295,0.0001018016,0.00002499793,0.0000878795,0.0001371631,0.0001186629],"domain_scores_gemma":[0.996538,0.001829546,0.0005855381,0.0001425435,0.0006589735,0.0002453411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000055299,0.00002591147,0.9772046,0.00002187411,0.00007506632,0.0001211763,0.0006868751,0.007144473,0.0001254587,0.001532439,0.0009957072,0.01201116],"study_design_scores_gemma":[0.000002651093,0.00001461966,0.9602476,0.00003193655,0.0000284549,0.00005910228,0.001119775,0.03629933,0.00008661456,0.0006171081,0.001477066,0.00001582473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908726,0.000411804,0.002270058,0.000422991,0.000008172156,0.00001810815,0.004084677,0.00002950601,0.001882211],"genre_scores_gemma":[0.9954823,0.0002841731,0.0008467677,0.00002626064,0.000005814677,0.000009745938,0.002660817,0.000007035452,0.0006771857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08633578,"threshold_uncertainty_score":0.1736884,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2002447070","doi":"10.4236/ojs.2015.51007","title":"Combining Likelihood Information from Independent Investigations","year":2015,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Likelihood function; Mathematics; Fisher information; Likelihood principle; Statistics; Maximum likelihood; Marginal likelihood; Scoring algorithm; Score test; Restricted maximum likelihood; Estimation theory; Likelihood-ratio test; Maximum likelihood sequence estimation; Expectation–maximization algorithm; Applied mathematics; Quasi-maximum likelihood","authors":[{"name":"Lai Jiang","is_ca":true},{"name":"Augustine Wong","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1376655204114027,"gpt":0.3801974429491913,"spread":0.2425319225377885,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04509996,0.002707231,0.004785608,0.01463876,0.001093738,0.00623958,0.003319268,0.003812833,0.004617136],"category_scores_gemma":[0.2047084,0.001760329,0.003309982,0.01064998,0.004071301,0.009065166,0.008192834,0.003812215,0.001848027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001471899,"about_ca_system_score_gemma":0.002571473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007997924,"about_ca_topic_score_gemma":0.000851803,"domain_scores_codex":[0.960347,0.02250233,0.002967481,0.004417901,0.009100731,0.0006644586],"domain_scores_gemma":[0.8665079,0.1048062,0.005929457,0.01194291,0.009996316,0.0008170712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006954225,0.0001470961,0.02005698,0.002248725,0.002156426,0.001859692,0.001255666,0.04205449,0.004454734,0.1440359,0.006228311,0.7748066],"study_design_scores_gemma":[0.0002043987,0.0004548098,0.01299997,0.0008987436,0.001793472,0.002308006,0.0004762299,0.2338227,0.009029038,0.7161564,0.02130185,0.0005542823],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005290166,0.001643915,0.9890149,0.000457732,0.0001112286,0.0002207477,0.0003035053,0.0002906244,0.002667198],"genre_scores_gemma":[0.2547922,0.003417385,0.7342627,0.0007370004,0.001093754,0.00130387,0.001505602,0.0002949398,0.002592376],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04509996,"threshold_uncertainty_score":0.2385142,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}