{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":83,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":83,"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":"78b517a19b76","filters":{"venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)"}},"results":[{"id":"W2753599755","doi":"10.1111/rssa.12378","title":"Visualization in Bayesian Workflow","year":2019,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Data Analysis with R","field":"Computer Science","cited_by":1128,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Office of Naval Research; Institute of Education Sciences; Defense Advanced Research Projects Agency; Columbia University; Alfred P. Sloan Foundation; National Science Foundation","keywords":"Workflow; Visualization; Computer science; Bayesian probability; Data science; Data mining; Artificial intelligence; Database","authors":[{"name":"Jonah Gabry","is_ca":false},{"name":"Daniel Simpson","is_ca":true},{"name":"Aki Vehtari","is_ca":false},{"name":"Michael Betancourt","is_ca":false},{"name":"Andrew Gelman","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.006838517424116364,"gpt":0.2549536180972047,"spread":0.2481151006730883,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01465472,0.002342244,0.001687293,0.006115708,0.001992852,0.01201606,0.003043093,0.00236057,0.06002238],"category_scores_gemma":[0.05234171,0.001439562,0.002551426,0.005135992,0.001556077,0.007012154,0.007331074,0.00392274,0.02300003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002060831,"about_ca_system_score_gemma":0.005130902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01020697,"about_ca_topic_score_gemma":0.007137607,"domain_scores_codex":[0.9916077,0.003925362,0.0009454367,0.001144424,0.00196623,0.0004108594],"domain_scores_gemma":[0.9712624,0.01536634,0.00116231,0.005855986,0.004672931,0.001679978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001488598,0.0002188651,0.002583315,0.001418867,0.0002643648,0.0009953964,0.003510327,0.02673417,0.00457187,0.2821173,0.3543637,0.3217332],"study_design_scores_gemma":[0.0002874541,0.00005563578,0.0008275891,0.0007457272,0.00006823903,0.0003946735,0.0003988755,0.1274019,0.005774612,0.4227192,0.4411002,0.0002257673],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001844198,0.0005382202,0.8621624,0.002870761,0.0004166167,0.0003349576,0.01000266,0.1083499,0.01348034],"genre_scores_gemma":[0.05494836,0.001495468,0.8795797,0.001371703,0.0003719446,0.001222674,0.02124356,0.0287029,0.01106366],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06002238,"threshold_uncertainty_score":0.2007949,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2133554893","doi":"10.1111/j.1467-985x.2012.01032.x","title":"Experimental Designs for Identifying Causal Mechanisms","year":2012,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":407,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"York University; National Science Foundation","keywords":"Causality (physics); Imperfect; Causation; Computer science; Causal model; Causal inference; Process (computing); Criticism; Key (lock); Natural (archaeology); Black box; Data science; Cognitive psychology; Psychology; Management science; Artificial intelligence; Epistemology; Econometrics; Engineering; Mathematics; Computer security","authors":[{"name":"Kosuke Imai","is_ca":false},{"name":"Dustin Tingley","is_ca":false},{"name":"Teppei Yamamoto","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1689160987547828,"gpt":0.425026705623513,"spread":0.2561106068687302,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1541085,0.001837296,0.002525386,0.003004183,0.001797654,0.003417612,0.0035656,0.004529509,0.01541494],"category_scores_gemma":[0.3901162,0.001220796,0.002600028,0.002907312,0.009954951,0.005753833,0.003969822,0.00673982,0.001440474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003276631,"about_ca_system_score_gemma":0.003578692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005908413,"about_ca_topic_score_gemma":0.0005012686,"domain_scores_codex":[0.7528006,0.2206811,0.006338624,0.008151219,0.01113389,0.0008945023],"domain_scores_gemma":[0.3808837,0.5377774,0.02820754,0.04051205,0.01131061,0.001308648],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000698287,0.0002222131,0.001556151,0.001579326,0.0004208351,0.00009496213,0.0007011333,0.007047759,0.0008679235,0.9384453,0.002684437,0.0456817],"study_design_scores_gemma":[0.001006394,0.001187538,0.001309478,0.0008108995,0.0002836515,0.0001020931,0.0002264296,0.02306491,0.001219303,0.9558483,0.01484455,0.00009643698],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008232003,0.001155884,0.9729522,0.00338905,0.0006158042,0.004423254,0.0005665064,0.0002550079,0.008410315],"genre_scores_gemma":[0.1332855,0.001061874,0.8303804,0.001560359,0.0005128513,0.03159438,0.0002669505,0.00007365017,0.001263942],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8458915,"threshold_uncertainty_score":0.8150133,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1931934008","doi":"10.1111/j.1467-985x.2010.00642.x","title":"Children’s Educational Progress: Partitioning Family, School and Area Effects","year":2010,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"School Choice and Performance","field":"Social Sciences","cited_by":111,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Economic and Social Research Council","keywords":"Variation (astronomy); Sibling; Pupil; Developmental psychology; Psychology; Multilevel model; Variance (accounting); Mathematics education; Statistics; Mathematics","authors":[{"name":"Jon Rasbash","is_ca":false},{"name":"George Leckie","is_ca":false},{"name":"Rebecca Pillinger","is_ca":false},{"name":"Jennifer M. Jenkins","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.008213977751724177,"gpt":0.285815936558515,"spread":0.2776019588067908,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01028564,0.001114357,0.00178042,0.002728626,0.001350918,0.002317274,0.00221305,0.001023881,0.004595137],"category_scores_gemma":[0.01754496,0.000665409,0.004058258,0.002855149,0.001806744,0.001319274,0.004193195,0.002424025,0.0003944666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00279657,"about_ca_system_score_gemma":0.002862692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1295278,"about_ca_topic_score_gemma":0.1060388,"domain_scores_codex":[0.9900412,0.006404334,0.0003455795,0.001547447,0.0007928962,0.00086859],"domain_scores_gemma":[0.9717498,0.02008909,0.002248073,0.002610709,0.001438945,0.001863327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006883777,0.0001750997,0.931151,0.0001386556,0.003708045,0.000269138,0.001531971,0.03144618,0.0004336037,0.005950849,0.001505117,0.02300204],"study_design_scores_gemma":[0.0001168667,0.0006573306,0.8411703,0.0001923299,0.00229407,0.0002577459,0.003154752,0.1361348,0.0008096065,0.01236477,0.002718121,0.0001292687],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9824089,0.0006800473,0.01452684,0.0005444837,0.00003139446,0.00005358529,0.0007872247,0.00006864614,0.0008988164],"genre_scores_gemma":[0.9916621,0.0001410964,0.006604844,0.00005979354,0.00001923129,0.00004374181,0.0009578562,0.00003981369,0.0004714537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1295278,"threshold_uncertainty_score":0.2575478,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3121682448","doi":"10.1111/j.1467-985x.2006.00425.x","title":"Sibling Death Clustering in India: State Dependence<i>Versus</i>Unobserved Heterogeneity","year":2006,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":62,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Economic and Social Research Council; University of Warwick; Royal Economic Society; McMaster University","keywords":"Sibling; Demography; Incidence (geometry); State (computer science); Psychology; Developmental psychology; Sociology; Mathematics","authors":[{"name":"Wiji Arulampalam","is_ca":false},{"name":"Sonia Bhalotra","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03711264889362167,"gpt":0.3150972871797946,"spread":0.2779846382861729,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001466669,0.0001128776,0.0003342802,0.001108201,0.0006117019,0.0009343486,0.000729723,0.0002368416,0.001365957],"category_scores_gemma":[0.004703818,0.0001926492,0.0006688078,0.001912879,0.001029512,0.0003521708,0.00113622,0.0005728441,0.00009036187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001143208,"about_ca_system_score_gemma":0.0007489413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06844198,"about_ca_topic_score_gemma":0.0810746,"domain_scores_codex":[0.9985281,0.0007422428,0.00009307118,0.0002208408,0.0001257397,0.0002899837],"domain_scores_gemma":[0.9949898,0.002276433,0.001418371,0.0007162969,0.0003755605,0.0002235045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007716803,0.00002841445,0.9843115,0.00003536502,0.0002176436,0.0002373855,0.001067807,0.003149068,0.0001444583,0.004242409,0.0004427384,0.006046043],"study_design_scores_gemma":[0.00000774578,0.00003115976,0.9854656,0.00001942518,0.0001424175,0.0003049124,0.002043164,0.008460352,0.0001911144,0.002872989,0.0004343966,0.00002659913],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997295,0.0001226248,0.001030914,0.0002848609,0.000004089517,0.000008494072,0.0002464367,0.00001231521,0.0009953042],"genre_scores_gemma":[0.9995579,0.00004700097,0.0001328101,0.00001901869,0.000002975072,0.000002679142,0.0001259009,0.000001412024,0.0001103754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06844198,"threshold_uncertainty_score":0.1360872,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3125079103","doi":"10.1111/rssa.12213","title":"Heads I win; Tails you lose: Asymmetry in Exchange rate Pass-through into Import Prices","year":2016,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":60,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Economics; Exchange-rate pass-through; Monetary economics; Currency; Quarter (Canadian coin); Exchange rate; Liberalization; Welfare; Market power; International economics; Microeconomics; Market economy","authors":[{"name":"Raphael Brun-Aguerre","is_ca":false},{"name":"Ana-Marı́a Fuertes","is_ca":false},{"name":"Matthew Greenwood‐Nimmo","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03144487830035606,"gpt":0.2492986596692874,"spread":0.2178537813689313,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001736191,0.0002723327,0.0004985257,0.001165781,0.0001775558,0.001512402,0.0002818774,0.000341115,0.003168517],"category_scores_gemma":[0.009376264,0.0001531186,0.0006653839,0.001016858,0.0005752035,0.001045378,0.0007520438,0.0008377898,0.0005804918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004466586,"about_ca_system_score_gemma":0.0003095858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007726335,"about_ca_topic_score_gemma":0.005400844,"domain_scores_codex":[0.9996213,0.00009389442,0.00003549747,0.0000706342,0.00007588776,0.0001027647],"domain_scores_gemma":[0.9908444,0.00430839,0.003358491,0.000677739,0.0005374685,0.0002735101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005998892,0.00004465085,0.9567258,0.0000461795,0.0003879016,0.0003453688,0.0004799533,0.02077265,0.0007079817,0.003088064,0.001825295,0.01497628],"study_design_scores_gemma":[0.00001988017,0.0001129775,0.9761541,0.00002936519,0.0001276293,0.0002231447,0.0005225681,0.01771047,0.0007458969,0.002711585,0.001614846,0.00002736296],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967662,0.0001331929,0.0005270977,0.0001230878,0.000003984061,0.000002980687,0.0007842543,0.00001946743,0.001639696],"genre_scores_gemma":[0.9981652,0.00005604866,0.00009331877,0.00001206985,0.00000662915,0.000001964846,0.0009789367,0.000007463497,0.0006784208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007726335,"threshold_uncertainty_score":0.01536274,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2738193654","doi":"10.1111/rssa.12306","title":"Poverty Mapping in Small Areas Under a Twofold Nested Error Regression Model","year":2017,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":59,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"National Research Council Canada","keywords":"Estimator; Small area estimation; Statistics; Econometrics; Mean squared error; Mathematics; Poverty; Estimation; Domain (mathematical analysis); Regression; Monte Carlo method; Standard error; Economics","authors":[{"name":"Yolanda Marhuenda García","is_ca":false},{"name":"Isabel Molina","is_ca":false},{"name":"Domingo Morales","is_ca":false},{"name":"J. N. K. Rao","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06765211363078552,"gpt":0.2678716173929229,"spread":0.2002195037621374,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01221509,0.0009083863,0.00200089,0.001279088,0.000440876,0.001624351,0.00278715,0.001284106,0.002726832],"category_scores_gemma":[0.02718835,0.0006398814,0.001619843,0.001371467,0.001329217,0.001880506,0.002783601,0.001449671,0.0004795292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007993128,"about_ca_system_score_gemma":0.0008209904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01185117,"about_ca_topic_score_gemma":0.00486236,"domain_scores_codex":[0.9924095,0.004906209,0.000252753,0.001292533,0.000623598,0.0005154994],"domain_scores_gemma":[0.9846683,0.009727743,0.002367882,0.001552057,0.001263598,0.0004203449],"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":[0.0004583098,0.0002082069,0.03204459,0.0001505094,0.0002545209,0.0007155513,0.0007773127,0.8531516,0.001463783,0.07756293,0.0009953295,0.03221739],"study_design_scores_gemma":[0.00001759043,0.00006014784,0.003956309,0.0000167115,0.00002555491,0.00005392553,0.00008505744,0.9790203,0.0001914953,0.0162129,0.000337036,0.00002302392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3675326,0.0003468705,0.6284643,0.0005421605,0.00004199534,0.0001215808,0.0005367326,0.0002619627,0.002151788],"genre_scores_gemma":[0.9090634,0.0002907194,0.08304223,0.00009546136,0.00003473811,0.0002733289,0.000675427,0.00007417096,0.006450412],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01221509,"threshold_uncertainty_score":0.06460035,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3213506774","doi":"10.1111/rssa.12696","title":"Combining Non-Probability and Probability Survey Samples Through Mass Imputation","year":2021,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":57,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"National Science Foundation","keywords":"Statistics; Probability mass function; Imputation (statistics); Estimator; Mathematics; Probability sampling; Probability distribution; Conditional probability; Population; Survey sampling; Sample (material); Econometrics; Missing data; Demography","authors":[{"name":"Jae Kwang Kim","is_ca":false},{"name":"Seho Park","is_ca":false},{"name":"Yilin Chen","is_ca":true},{"name":"Changbao Wu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06967204401665635,"gpt":0.3486969212721688,"spread":0.2790248772555125,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05634809,0.001005142,0.002654043,0.002818819,0.001002278,0.003182148,0.003492424,0.001821933,0.002962267],"category_scores_gemma":[0.1395271,0.0009468141,0.001759361,0.00488465,0.001605352,0.002913206,0.004149188,0.002323072,0.0007078956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001118801,"about_ca_system_score_gemma":0.001251154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003223506,"about_ca_topic_score_gemma":0.002645723,"domain_scores_codex":[0.9581997,0.0339025,0.001100581,0.002724573,0.00346798,0.0006045949],"domain_scores_gemma":[0.8832322,0.08914158,0.006954684,0.01512561,0.004971721,0.0005741713],"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":[0.001264901,0.0008370519,0.1054105,0.0008121034,0.002568235,0.001548795,0.002642899,0.2376802,0.001399576,0.2744423,0.006778867,0.3646145],"study_design_scores_gemma":[0.000192107,0.0005172647,0.01828525,0.0002403021,0.0005025086,0.000307856,0.0004353219,0.6481192,0.001692782,0.3227662,0.006863767,0.00007741384],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04535054,0.0003082704,0.9514921,0.0004371185,0.00008355651,0.0004499749,0.0002953672,0.0001660893,0.001417034],"genre_scores_gemma":[0.5796529,0.0003735595,0.4149559,0.000364989,0.0002066797,0.001178136,0.001147983,0.00006430248,0.00205562],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05634809,"threshold_uncertainty_score":0.2980008,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1900844198","doi":"10.1111/j.1467-985x.2010.00684.x","title":"A New Look at Halley’s Life Table","year":2011,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":49,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"Social Sciences and Humanities Research Council of Canada; University of Cambridge; Royal Society","keywords":"Table (database); Presentation (obstetrics); Context (archaeology); Outlier; Mathematics; Computer science; History; Statistics","authors":[{"name":"David R. Bellhouse","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02445325463134244,"gpt":0.269093010632352,"spread":0.2446397560010096,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004855993,0.0004937266,0.0007296253,0.006088177,0.001983258,0.005685891,0.0008030024,0.001038604,0.02656643],"category_scores_gemma":[0.04189866,0.0003382842,0.0004396976,0.00837949,0.002363822,0.007716058,0.001847178,0.004195082,0.004151772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003827766,"about_ca_system_score_gemma":0.002632236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01633163,"about_ca_topic_score_gemma":0.01050189,"domain_scores_codex":[0.9960992,0.001902369,0.0003765478,0.0004287019,0.000969561,0.0002236385],"domain_scores_gemma":[0.9810776,0.01264682,0.0009032297,0.000988059,0.003533449,0.0008508508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00004949304,0.000008910297,0.001198243,0.0001117342,0.00001455642,0.0000725373,0.001101606,0.0003000823,0.00002461989,0.2251466,0.6898323,0.08213934],"study_design_scores_gemma":[0.000003199224,0.0000121487,0.0009212548,0.0001922168,0.000003884785,0.00007176659,0.0003358499,0.0001223025,0.00002825464,0.04635853,0.9519271,0.00002349753],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.009070078,0.1154178,0.035231,0.5786572,0.0486329,0.0001083958,0.01882737,0.001030443,0.1930248],"genre_scores_gemma":[0.3162337,0.1467652,0.0621363,0.129386,0.09171738,0.0004895381,0.02229341,0.002414243,0.2285644],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02656643,"threshold_uncertainty_score":0.08887362,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2067860133","doi":"10.1111/1467-985x.00279","title":"Social Identities and Political Cleavages: The Role of Political Context","year":2003,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":45,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Western University","funders":"Economic and Social Research Council; York University; University of Essex","keywords":"Voting; Politics; Voting behavior; Context (archaeology); Political science; Competition (biology); Political economy; Social class; Diversity (politics); Variety (cybernetics); Social group; Sociology; Social science; Geography","authors":[{"name":"Robert Andersen","is_ca":true},{"name":"Anthony Heath","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02145206295281114,"gpt":0.3219491311063992,"spread":0.300497068153588,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003615103,0.0002534126,0.00063703,0.0009444369,0.001130421,0.002557508,0.0004984527,0.0003518582,0.006070821],"category_scores_gemma":[0.01882895,0.0001458674,0.0004996303,0.00114434,0.001970239,0.0009039384,0.002306508,0.001323667,0.0003420581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005414872,"about_ca_system_score_gemma":0.0004209707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002892806,"about_ca_topic_score_gemma":0.003658287,"domain_scores_codex":[0.9932782,0.005090569,0.000200112,0.0005406886,0.0005693262,0.0003211632],"domain_scores_gemma":[0.96931,0.02091357,0.005860465,0.001838092,0.0006875508,0.001390202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007100715,0.0001768824,0.9442477,0.00009726838,0.0005281729,0.0003358246,0.003907498,0.00118089,0.002819614,0.0159654,0.0006474863,0.02938314],"study_design_scores_gemma":[0.00003587403,0.0002510855,0.9756078,0.00007093183,0.0001826632,0.0001976556,0.003937618,0.00471359,0.0009888833,0.01127203,0.002714586,0.00002726723],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929798,0.000259062,0.00206074,0.000310038,0.00002426153,0.00001486603,0.000119233,0.000005094123,0.004227015],"genre_scores_gemma":[0.9993388,0.00003203617,0.0003865353,0.00001538206,0.00001395102,0.000007294599,0.000034094,0.000002887188,0.0001688812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006070821,"threshold_uncertainty_score":0.02030891,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2053177811","doi":"10.1111/j.1467-985x.2006.00416.x","title":"Estimating the Prevalence of Male Clients of Prostitute Women in Vancouver With a Simple Capture–Recapture Method","year":2006,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Census and Population Estimation","field":"Mathematics","cited_by":41,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Mark and recapture; Simple (philosophy); Population size; Demography; Population; Statistics; Focus (optics); Computer science; Geography; Mathematics; Sociology","authors":[{"name":"John M. Roberts","is_ca":false},{"name":"Devon D. Brewer","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0148457697200818,"gpt":0.3009016288150596,"spread":0.2860558590949778,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008255395,0.0002683633,0.0004682913,0.002066916,0.0005929489,0.0007005552,0.0007785436,0.0003774416,0.001292733],"category_scores_gemma":[0.00515177,0.0003654064,0.0002710721,0.001303833,0.0002672129,0.0002004528,0.0006607994,0.0004186622,0.0002365574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001775622,"about_ca_system_score_gemma":0.00109614,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5585247,"about_ca_topic_score_gemma":0.6280148,"domain_scores_codex":[0.9994822,0.0001617553,0.00004827338,0.0001045947,0.0001440876,0.0000591784],"domain_scores_gemma":[0.9983296,0.00065171,0.0002620091,0.0001795278,0.0004844913,0.00009263006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001246697,0.00007761244,0.8852048,0.0001632159,0.0001980788,0.0004882067,0.001179627,0.01453501,0.003470335,0.002338598,0.001836929,0.09038278],"study_design_scores_gemma":[0.00002114815,0.00004893974,0.9388311,0.00006858246,0.00005192079,0.0004247133,0.0008390391,0.05504945,0.0007746789,0.001261204,0.002596804,0.00003230502],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981917,0.0004390606,0.01296597,0.0001515327,0.00001096136,0.0001407651,0.001776513,0.00006567403,0.002532559],"genre_scores_gemma":[0.9842818,0.0003285476,0.01203929,0.00002306482,0.000007332897,0.00006392528,0.001468122,0.000007402656,0.001780399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4414753,"threshold_uncertainty_score":0.8881505,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2035509585","doi":"10.1111/1467-985x.00275","title":"Communicating the Risks Arising from Geohazards","year":2003,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Natural Environment Research Council; Trent University; British Geological Survey; Nottingham Trent University","keywords":"Geohazard; Terminology; Natural (archaeology); Process (computing); Common ground; Risk analysis (engineering); Outcome (game theory); Risk management; Business; Environmental planning; Environmental resource management; Computer science; Geography; Engineering; Psychology; Social psychology; Environmental science; Linguistics; Economics","authors":[{"name":"Michael Rosenbaum","is_ca":false},{"name":"M. G. Culshaw","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02795823199036485,"gpt":0.281206710272089,"spread":0.2532484782817241,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02620226,0.0008260525,0.0006469166,0.001838455,0.002816904,0.009067776,0.001230976,0.004877403,0.01306318],"category_scores_gemma":[0.1214721,0.0004514884,0.0004445984,0.00122488,0.00287548,0.007747879,0.006964877,0.004629698,0.003126767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002296925,"about_ca_system_score_gemma":0.003253006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001213965,"about_ca_topic_score_gemma":0.0006749652,"domain_scores_codex":[0.9665654,0.02290114,0.002260569,0.0007565413,0.00646093,0.001055346],"domain_scores_gemma":[0.8191115,0.1402723,0.01925898,0.006497479,0.01231592,0.002543833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006406418,0.000286531,0.02651346,0.001488337,0.0002136276,0.003669651,0.06255119,0.008822843,0.003803109,0.2749679,0.2204547,0.396588],"study_design_scores_gemma":[0.000066237,0.0006091622,0.008878245,0.003441158,0.0002455444,0.003363749,0.04228203,0.01266946,0.006942333,0.4154986,0.5056815,0.0003218722],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1634825,0.01694859,0.1217931,0.493217,0.006990999,0.0003665072,0.0009407107,0.0008102777,0.1954503],"genre_scores_gemma":[0.958606,0.006184808,0.01001065,0.007311606,0.00337206,0.0001430036,0.0002210755,0.00009371805,0.0140572],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02620226,"threshold_uncertainty_score":0.1385725,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3121892662","doi":"10.1111/j.1467-985x.2011.01009.x","title":"Charitable Giving for Overseas Development: UK Trends over a Quarter Century","year":2011,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Religion, Society, and Development","field":"Social Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Natural Environment Research Council; Economic and Social Research Council","keywords":"Quarter (Canadian coin); Government (linguistics); Economic growth; Emergency relief; Political science; Economics; Business; Emergency management; Geography","authors":[{"name":"Anthony B. Atkinson","is_ca":false},{"name":"Peter Backus","is_ca":false},{"name":"John Micklewright","is_ca":false},{"name":"Cathy Pharoah","is_ca":false},{"name":"Sylke V. Schnepf","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02500919178106024,"gpt":0.2836125767534197,"spread":0.2586033849723594,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001792793,0.0002800059,0.0004040412,0.003711967,0.0002920751,0.001683742,0.0003332394,0.0006794096,0.006926158],"category_scores_gemma":[0.00891804,0.0002032691,0.000315636,0.01094251,0.000509191,0.001276151,0.001457758,0.001103903,0.001490108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00291445,"about_ca_system_score_gemma":0.001795683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0774607,"about_ca_topic_score_gemma":0.08132274,"domain_scores_codex":[0.9979934,0.0003350651,0.0004824003,0.000343159,0.0005337577,0.0003123758],"domain_scores_gemma":[0.9810537,0.002688948,0.009125924,0.0007508434,0.00452795,0.001852734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006198898,0.00007695096,0.6500335,0.00218661,0.0001800972,0.000593181,0.005076139,0.001046091,0.0008963521,0.003617922,0.06329997,0.2723733],"study_design_scores_gemma":[0.00001066198,0.00009537579,0.9185998,0.0006018371,0.00002440699,0.0003641172,0.002034739,0.0001856624,0.000231212,0.0001043894,0.0777209,0.00002690919],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8287876,0.07159906,0.0008524676,0.03462015,0.001511241,0.00004833302,0.03286728,0.0001772528,0.02953658],"genre_scores_gemma":[0.9468848,0.02982023,0.0005094313,0.002478354,0.0005716553,0.00004118415,0.007877151,0.00006821565,0.01174905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0774607,"threshold_uncertainty_score":0.1540197,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2460744065","doi":"10.1111/rssa.12208","title":"Retail Payment Innovations and Cash usage: Accounting for Attrition by using Refreshment Samples","year":2016,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":35,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Bank of Canada","funders":"","keywords":"Point of sale; Payment; Cash; Attrition; Pace; Business; Point (geometry); Value (mathematics); ATM card; Finance; Computer science","authors":[{"name":"Heng Chen","is_ca":true},{"name":"Marie‐Hélène Felt","is_ca":true},{"name":"Kim P. Huynh","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03327886037364827,"gpt":0.2449445204461171,"spread":0.2116656600724688,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.08014492,0.000600593,0.001061422,0.001932884,0.001020887,0.002361247,0.003692734,0.001291068,0.006976328],"category_scores_gemma":[0.2063191,0.0006345801,0.002775667,0.003486844,0.001371011,0.002521626,0.002427489,0.002808847,0.001325523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001067176,"about_ca_system_score_gemma":0.001736749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01898,"about_ca_topic_score_gemma":0.01197856,"domain_scores_codex":[0.9514295,0.03357159,0.003563226,0.004364211,0.004698968,0.002372504],"domain_scores_gemma":[0.6736568,0.2103131,0.04060638,0.063183,0.0100781,0.002162641],"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":[0.001251684,0.0003361554,0.9122474,0.0002162798,0.002939168,0.0003097991,0.001392388,0.01452735,0.0003867561,0.005422947,0.005684663,0.05528533],"study_design_scores_gemma":[0.0002394278,0.001400443,0.8367201,0.0002977285,0.002571175,0.0003769934,0.001762923,0.1247223,0.003498468,0.01611784,0.01209505,0.0001975995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8951762,0.0007470626,0.09326101,0.001215942,0.000174188,0.0006774778,0.00387367,0.0004982697,0.004376064],"genre_scores_gemma":[0.9832773,0.00008623421,0.01122897,0.0001540222,0.00005682902,0.0003802398,0.0024348,0.00009185039,0.00228985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08014492,"threshold_uncertainty_score":0.4238519,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2961984786","doi":"10.1111/rssa.12491","title":"UK Regional Nowcasting Using a Mixed Frequency Vector Auto-Regressive Model with Entropic Tilting","year":2019,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Grey System Theory Applications","field":"Decision Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Blackberry (Canada)","funders":"","keywords":"Nowcasting; Autoregressive model; Aggregate (composite); Econometrics; Computer science; Exploit; Vector autoregression; Economics; Geography; Meteorology","authors":[{"name":"Gary Koop","is_ca":true},{"name":"Stuart McIntyre","is_ca":false},{"name":"James Mitchell","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05528175492662648,"gpt":0.3289328123172136,"spread":0.2736510573905871,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001836178,0.000477725,0.0006089285,0.0005521775,0.0001896178,0.001282778,0.0009080258,0.0009043352,0.002240449],"category_scores_gemma":[0.007864974,0.0004882351,0.0007984948,0.0008051501,0.0003975992,0.001253174,0.0007015429,0.001322842,0.000396744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008543151,"about_ca_system_score_gemma":0.0008951657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05175754,"about_ca_topic_score_gemma":0.03714771,"domain_scores_codex":[0.9994414,0.000222982,0.00004104665,0.0001471748,0.00009574417,0.00005151605],"domain_scores_gemma":[0.9981381,0.0009185531,0.0003299875,0.0002403488,0.0003054398,0.00006759705],"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":[0.00006137028,0.00001148172,0.002609032,0.00003144251,0.00004963196,0.00005985575,0.00005829248,0.9683073,0.0008661644,0.01181648,0.001308036,0.01482091],"study_design_scores_gemma":[0.00000283312,0.000005349711,0.000525454,0.000003337314,0.000005800674,0.000003717838,0.0000057129,0.997277,0.0001334919,0.001640452,0.0003897865,0.000007072988],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.235489,0.000530055,0.7543297,0.00140067,0.0003790301,0.00005465306,0.002007306,0.001105615,0.004703977],"genre_scores_gemma":[0.9448943,0.000295843,0.0486536,0.0001229213,0.0001317166,0.00004347489,0.001354882,0.0001339269,0.004369327],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05175754,"threshold_uncertainty_score":0.1029125,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1987320903","doi":"10.1111/rssa.12036","title":"Average Household Size and the Eradication of Malaria","year":2013,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Mosquito-borne diseases and control","field":"Medicine","cited_by":31,"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":"Malaria; Dengue fever; Environmental health; Demography; Geography; Medicine; Virology; Immunology","authors":[{"name":"Lena Huldén","is_ca":false},{"name":"Ross McKitrick","is_ca":true},{"name":"Larry Huldén","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.005817521407905111,"gpt":0.2225979709197739,"spread":0.2167804495118688,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001087085,0.00008883238,0.0002666921,0.0003749696,0.0001136073,0.0003273789,0.0002457738,0.000209125,0.003630534],"category_scores_gemma":[0.007992042,0.00005843597,0.000202472,0.0004240084,0.0003979328,0.0003923046,0.000390615,0.0004181445,0.0001474742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002124378,"about_ca_system_score_gemma":0.0001204944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001209087,"about_ca_topic_score_gemma":0.0009375964,"domain_scores_codex":[0.999537,0.0002433315,0.00002617618,0.0000627443,0.00006117205,0.00006958919],"domain_scores_gemma":[0.9887311,0.004907602,0.004495264,0.0004080373,0.0003303514,0.00112759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003603641,0.00006328309,0.9655025,0.00008403154,0.0003425174,0.0001560045,0.00009583624,0.003643417,0.0003436299,0.002741402,0.00297753,0.0236895],"study_design_scores_gemma":[0.00001826781,0.0002075956,0.9912853,0.00003631789,0.00008010953,0.0003314516,0.0001640886,0.003045854,0.0001629362,0.003212937,0.001445573,0.000009603993],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882209,0.003390572,0.0006504796,0.002251954,0.00005669021,0.000005635979,0.0005954473,0.00002028075,0.004808071],"genre_scores_gemma":[0.9995289,0.0001632497,0.00004819054,0.00004384515,0.00003693744,0.000001294304,0.00008859743,0.000001194737,0.00008784208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003630534,"threshold_uncertainty_score":0.0121454,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4309558893","doi":"10.1111/rssa.12955","title":"Estimation of Reproduction Numbers in Real Time: Conceptual and Statistical Challenges","year":2022,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":30,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"NIHR Cambridge Biomedical Research Centre; Economic and Social Research Council; Engineering and Physical Sciences Research Council; Chief Scientist Office, Scottish Government Health and Social Care Directorate; Defence Science and Technology Laboratory; Medical Research Council Canada; Public Health England; Public Health Agency; National Institute for Health Research Health Protection Research Unit; University of Warwick; Royal Society; Department of Health and Social Care; Defence Science and Technology Group; Alan Turing Institute; Health and Social Care Research and Development Division; National Institute for Health and Care Research; Scottish Government; British Heart Foundation; Wellcome Trust; Medical Research Council; Alexander von Humboldt-Stiftung","keywords":"Computer science; Intuition; Data science; Coronavirus disease 2019 (COVID-19); Metric (unit); Pandemic; Operations research; Aggregate data; Econometrics; Economics; Statistics; Mathematics; Operations management; Infectious disease (medical specialty); Psychology","authors":[{"name":"Lorenzo Pellis","is_ca":false},{"name":"Paul Birrell","is_ca":false},{"name":"Joshua Blake","is_ca":false},{"name":"Christopher E. Overton","is_ca":false},{"name":"Francesca Scarabel","is_ca":false},{"name":"Helena B. Stage","is_ca":false},{"name":"Ellen Brooks‐Pollock","is_ca":false},{"name":"León Danon","is_ca":false},{"name":"Ian Hall","is_ca":false},{"name":"Thomas House","is_ca":false},{"name":"Matt J. Keeling","is_ca":false},{"name":"Jonathan M. Read","is_ca":false},{"name":"Daniela De Angelis","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09792103860554488,"gpt":0.3745656238347784,"spread":0.2766445852292335,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05943691,0.0007581045,0.001780727,0.002564486,0.0009042589,0.005655804,0.004596732,0.002877758,0.002587988],"category_scores_gemma":[0.3253201,0.0009586196,0.001179648,0.003281871,0.007717143,0.008576212,0.004226585,0.008033656,0.0006404812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002593988,"about_ca_system_score_gemma":0.001708526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007567397,"about_ca_topic_score_gemma":0.002421509,"domain_scores_codex":[0.9659354,0.02729964,0.001278468,0.002691221,0.002343539,0.0004517765],"domain_scores_gemma":[0.6166804,0.3491781,0.0132374,0.01493344,0.005170733,0.0007999504],"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":[0.00006778952,0.00003706478,0.01127867,0.0005056277,0.0001720841,0.0002558013,0.00100855,0.1080627,0.0002705374,0.8274456,0.008787069,0.04210849],"study_design_scores_gemma":[0.00001712997,0.00003759071,0.002195221,0.0002781657,0.00001622637,0.0001886955,0.0002393102,0.1672345,0.0002070664,0.8220488,0.007480846,0.0000562986],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01762838,0.006566925,0.9450577,0.02408412,0.0005622067,0.0001099236,0.000865815,0.0001975098,0.004927409],"genre_scores_gemma":[0.7196212,0.0068239,0.2592528,0.00417182,0.003024302,0.0009268461,0.001485011,0.0002811268,0.004413076],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05943691,"threshold_uncertainty_score":0.3143361,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2109880956","doi":"10.1111/j.1467-985x.2011.01012.x","title":"Assessing Gross Domestic Product and Inflation Probability Forecasts Derived from Bank of England Fan Charts","year":2011,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":30,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"HEC Montréal; McGill University","funders":"","keywords":"Inflation (cosmology); Econometrics; Economics; Product (mathematics); Gross domestic product; Quarter (Canadian coin); Calibration; Consensus forecast; Real gross domestic product; Statistics; Mathematics; Macroeconomics; Geography","authors":[{"name":"John W. Galbraith","is_ca":true},{"name":"Simon van Norden","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0739803070320568,"gpt":0.2531540271720057,"spread":0.1791737201399489,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01021736,0.000499247,0.000517576,0.003002627,0.0001882627,0.001788165,0.0005051403,0.0008990686,0.00264854],"category_scores_gemma":[0.1206351,0.0003661262,0.0003377277,0.002808439,0.0005223468,0.002144022,0.0008348659,0.0007756877,0.0008036535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001221337,"about_ca_system_score_gemma":0.0007177503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02934258,"about_ca_topic_score_gemma":0.01288245,"domain_scores_codex":[0.9956989,0.0018352,0.0004127521,0.0005485271,0.001329547,0.0001750865],"domain_scores_gemma":[0.8692112,0.09665406,0.01425326,0.004473424,0.01455496,0.0008531166],"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":[0.001005701,0.00006710774,0.5873787,0.0003454976,0.0003891434,0.0004582546,0.001829463,0.2994386,0.0007109956,0.01848434,0.01789486,0.07199751],"study_design_scores_gemma":[0.00009656089,0.0002144756,0.3756787,0.0001620988,0.0001196728,0.0002425631,0.0008776969,0.6005572,0.001959248,0.01034344,0.009563113,0.0001852579],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9556705,0.0005408156,0.02648102,0.0005367667,0.00008384808,0.00006332748,0.007211202,0.0004061465,0.009006351],"genre_scores_gemma":[0.9900359,0.0001463097,0.004137382,0.0000198686,0.000033266,0.00001866716,0.005103448,0.00002737984,0.0004777279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02934258,"threshold_uncertainty_score":0.05834359,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4281743231","doi":"10.1111/rssa.12849","title":"Nonlinear Modal Regression for Dependent Data with Application for Predicting Covid-19","year":2022,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":30,"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":"Nonlinear system; Estimator; Nonlinear regression; Consistency (knowledge bases); Modal; Regression; Mathematics; Applied mathematics; Regression analysis; Statistics; Computer science; Physics","authors":[{"name":"Aman Ullah","is_ca":false},{"name":"Tao Wang","is_ca":true},{"name":"Weixin Yao","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.146800291078911,"gpt":0.4254930260368877,"spread":0.2786927349579766,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00306864,0.0008352721,0.0005956738,0.0008015415,0.0003532062,0.000578132,0.001241057,0.000936034,0.001771159],"category_scores_gemma":[0.01268813,0.0003802133,0.0009291738,0.0006264306,0.0006103427,0.001116345,0.001110958,0.001623604,0.0003542995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005975634,"about_ca_system_score_gemma":0.0006716957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007173842,"about_ca_topic_score_gemma":0.004608078,"domain_scores_codex":[0.9991812,0.0003868286,0.00003482112,0.000197484,0.0001502487,0.00004949046],"domain_scores_gemma":[0.996078,0.002821589,0.0003468331,0.0002369102,0.0004586128,0.0000580997],"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":[0.0001119232,0.00007355882,0.007584065,0.0000823036,0.00007314581,0.0001141161,0.00007520381,0.9296278,0.003112074,0.01245388,0.0005756837,0.04611626],"study_design_scores_gemma":[0.000001171947,0.000006634898,0.0002865732,0.000001693541,0.000002115534,0.00000366986,0.000003390287,0.9986267,0.000202807,0.0007939048,0.00006809249,0.000003323312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0508552,0.0001157299,0.9477489,0.0001799849,0.0000261548,0.00003615766,0.00009613662,0.0002767023,0.0006649581],"genre_scores_gemma":[0.8468451,0.0002268143,0.1494298,0.0001429979,0.00005881405,0.0001432441,0.0004305445,0.00009340861,0.002629176],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007173842,"threshold_uncertainty_score":0.01622874,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1986493256","doi":"10.1111/j.1467-985x.2005.00380.x","title":"Comparing Clinical Data with Administrative Data for Producing Acute Myocardial Infarction Report Cards","year":2005,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":29,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Sunnybrook Health Science Centre; Institute for Clinical Evaluative Sciences; Women's College Hospital; University of Toronto","funders":"Canadian Institutes of Health Research; Institute for Clinical Evaluative Sciences; Heart and Stroke Foundation of Canada","keywords":"Decile; Medicine; Myocardial infarction; Emergency medicine; Standardization; Medical emergency; Internal medicine; Statistics; Computer science","authors":[{"name":"Peter C. Austin","is_ca":true},{"name":"Jack V. Tu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1825449441704811,"gpt":0.3958244817509159,"spread":0.2132795375804347,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06493086,0.0005592755,0.0007822854,0.006781608,0.0006532578,0.004397995,0.001801955,0.0008421976,0.001659633],"category_scores_gemma":[0.3210018,0.0005978166,0.0007618567,0.01553788,0.0008418534,0.001586072,0.001893097,0.0009158471,0.0006537311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005472642,"about_ca_system_score_gemma":0.00564375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.103921,"about_ca_topic_score_gemma":0.07101297,"domain_scores_codex":[0.8889118,0.07346696,0.006775097,0.003124204,0.02600479,0.001717095],"domain_scores_gemma":[0.6316817,0.2314613,0.05057035,0.02439479,0.05760603,0.004285729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001327859,0.0002156671,0.9630563,0.0002478363,0.000672141,0.0000804493,0.0004261088,0.00451947,0.0001535356,0.001606596,0.004290147,0.02340388],"study_design_scores_gemma":[0.0005026609,0.0007313163,0.9632193,0.0002440565,0.000384411,0.0001214339,0.00118585,0.02479724,0.0008092718,0.000991818,0.006941391,0.00007125542],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9440082,0.001462029,0.00983082,0.002373899,0.0002180343,0.000704992,0.03307047,0.000165637,0.008165939],"genre_scores_gemma":[0.9701006,0.0003293646,0.007904315,0.0001836443,0.00007927392,0.0002249757,0.02085721,0.00002851595,0.0002922298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.103921,"threshold_uncertainty_score":0.3433914,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2108722353","doi":"10.1111/j.1467-985x.2006.00397.x","title":"Public Expenditure in the UK: How Measures Matter","year":2006,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":28,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Nuffield Foundation","keywords":"Microdata (statistics); Treasury; Public expenditure; Economics; Public spending; Actuarial science; Statistics; Econometrics; Public finance; Demography; Census; Sociology; Mathematics; Political science; Law; Macroeconomics","authors":[{"name":"Stuart Soroka","is_ca":true},{"name":"Christopher Wlezien","is_ca":false},{"name":"Iain McLean","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03276078451644698,"gpt":0.2164618935704111,"spread":0.1837011090539641,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004231925,0.0003660949,0.00060199,0.005456818,0.0003133926,0.003374157,0.0004757427,0.000350965,0.009672472],"category_scores_gemma":[0.05552349,0.0001951301,0.0004441439,0.0187396,0.0009851354,0.002483408,0.001734029,0.0006720953,0.001318669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004075782,"about_ca_system_score_gemma":0.001243198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08354876,"about_ca_topic_score_gemma":0.08185784,"domain_scores_codex":[0.994433,0.002381671,0.000850283,0.0005575297,0.00134842,0.0004290809],"domain_scores_gemma":[0.9528888,0.02512427,0.01084417,0.002233458,0.008086799,0.0008224309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004933182,0.00003194488,0.7352324,0.00157137,0.0006326923,0.0002153157,0.003103676,0.002794957,0.0001335902,0.03318951,0.06529912,0.1573021],"study_design_scores_gemma":[0.00001395423,0.00006684624,0.963137,0.0009272847,0.0001228342,0.0001009562,0.00290603,0.0008008647,0.00009750505,0.0035168,0.02827116,0.00003861031],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7550653,0.05335879,0.003884358,0.03535018,0.0009488619,0.00007787051,0.05257364,0.0001526388,0.09858835],"genre_scores_gemma":[0.9806094,0.00815565,0.0005365785,0.0005498094,0.000251153,0.0000550246,0.006921772,0.00005871914,0.002862036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08354876,"threshold_uncertainty_score":0.1661249,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2108898395","doi":"10.1111/j.1467-985x.2012.01071.x","title":"Quantifying the Effect of Area Deprivation on Child Pedestrian Casualties by Using Longitudinal Mixed Models to Adjust for Confounding, Interference and Spatial Dependence","year":2012,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Traffic and Road Safety","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Covariate; Confounding; Pedestrian; Bayesian probability; Geography; Econometrics; Statistics; Demography; Mathematics","authors":[{"name":"Daniel J. Graham","is_ca":false},{"name":"Emma J. McCoy","is_ca":false},{"name":"David A. Stephens","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04290797963869458,"gpt":0.2869657483664507,"spread":0.2440577687277561,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03925895,0.0009725324,0.000928771,0.00191214,0.0006908064,0.001673927,0.001587701,0.0008522447,0.002091236],"category_scores_gemma":[0.06034318,0.0007923159,0.003853496,0.002270864,0.0008972971,0.001115425,0.002885343,0.001356575,0.0002289494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001349994,"about_ca_system_score_gemma":0.001988736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03980694,"about_ca_topic_score_gemma":0.03998622,"domain_scores_codex":[0.973919,0.02239807,0.0007911198,0.001372501,0.0009423436,0.0005769015],"domain_scores_gemma":[0.8932819,0.08610632,0.01052075,0.007129597,0.002005602,0.0009558063],"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":[0.0006993453,0.00009433026,0.9090386,0.000130395,0.004578541,0.0001900429,0.000440069,0.06160549,0.0004965641,0.003257595,0.0004051518,0.01906384],"study_design_scores_gemma":[0.000100001,0.001490054,0.5456615,0.0001866182,0.002830834,0.0002542913,0.0009279929,0.432512,0.001404088,0.01169959,0.002819936,0.0001131413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8861973,0.0009414734,0.110226,0.0005411707,0.00004200583,0.00008100489,0.0007334329,0.0001351864,0.001102401],"genre_scores_gemma":[0.9799705,0.0001607684,0.01860795,0.00006231559,0.00002570202,0.0001054236,0.0005641082,0.0000260797,0.0004771894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03980694,"threshold_uncertainty_score":0.2076236,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2138410354","doi":"10.1111/j.1467-985x.2004.00345.x","title":"A Comparison Study of Realtime Fatality Rates: Severe Acute Respiratory Syndrome in Hong Kong, Singapore, Taiwan, Toronto and Beijing, China","year":2004,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Beijing; China; Case fatality rate; Medicine; Respiratory system; Pediatrics; Emergency medicine; Geography; Epidemiology; Internal medicine","authors":[{"name":"Paul Yip","is_ca":false},{"name":"Kwok Fai Lam","is_ca":false},{"name":"Eric H. Y. Lau","is_ca":false},{"name":"Pui Hing Chau","is_ca":false},{"name":"Kenneth W. Tsang","is_ca":false},{"name":"Anne Chao","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03072880418408521,"gpt":0.3707029556835734,"spread":0.3399741514994882,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001646646,0.0004890798,0.0003448188,0.001272036,0.000393034,0.0007557127,0.000521423,0.0003744733,0.0008985085],"category_scores_gemma":[0.004554384,0.0001682838,0.0004828295,0.001719011,0.0005724579,0.0005331976,0.0005671735,0.0003466714,0.0001138275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003194192,"about_ca_system_score_gemma":0.001734257,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3753799,"about_ca_topic_score_gemma":0.3032182,"domain_scores_codex":[0.999121,0.0003057409,0.0001195638,0.0001549997,0.0001418575,0.0001568344],"domain_scores_gemma":[0.9953986,0.001292707,0.001314078,0.0003667949,0.0008722506,0.0007555794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003795357,0.00003226459,0.9938053,0.00004968293,0.0002141142,0.0003986214,0.0008773528,0.001365611,0.0002331829,0.000174294,0.0003065827,0.002163397],"study_design_scores_gemma":[0.000009974069,0.0001133421,0.996303,0.000006420175,0.00003733058,0.0001109715,0.001163369,0.001960091,0.0001052264,0.00002130559,0.0001565247,0.00001255681],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999139,0.00008895758,0.00005069245,0.00002644053,0.000002842261,0.000005160102,0.000435387,0.000002744597,0.0002488494],"genre_scores_gemma":[0.9988853,0.00005574387,0.00002794186,0.000007049687,0.000002891635,0.000003999139,0.0008419739,0.00000123643,0.0001738888],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6246201,"threshold_uncertainty_score":0.74639,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2004761633","doi":"10.1111/rssa.12026","title":"Florence Nightingale, statistics and the Crimean War","year":2013,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Historical Studies on Reproduction, Gender, Health, and Societal Changes","field":"Arts and Humanities","cited_by":26,"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":"University of Warwick","keywords":"History; Statistical analysis; Spanish Civil War; First world war; World War II; Demography; Classics; Statistics; Ancient history; Sociology; Archaeology; Mathematics","authors":[{"name":"Lynn McDonald","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02375687317279756,"gpt":0.2409771018575765,"spread":0.2172202286847789,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.004493192,0.0005354701,0.0005537936,0.006068266,0.003316654,0.004874391,0.0008334797,0.001312038,0.006253387],"category_scores_gemma":[0.02747382,0.0003667288,0.0002310198,0.006620587,0.006072901,0.004308133,0.001496767,0.004433357,0.001119455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007002936,"about_ca_system_score_gemma":0.004409874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1135289,"about_ca_topic_score_gemma":0.0933155,"domain_scores_codex":[0.9969415,0.001241921,0.0001871221,0.0002902063,0.001093975,0.0002451642],"domain_scores_gemma":[0.9780492,0.0155572,0.001104465,0.0007048705,0.003424645,0.001159499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009320348,0.000005056538,0.0009084097,0.00005168186,0.000005249375,0.00004150537,0.0007917575,0.00009251668,0.00001170951,0.05480848,0.9252772,0.01799701],"study_design_scores_gemma":[0.000003175253,0.000009675439,0.004579936,0.0003362616,0.00000301838,0.00009017551,0.001220736,0.00009682617,0.00005024655,0.01412375,0.9794624,0.00002378827],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.003565235,0.1302289,0.0008307681,0.8141091,0.01362798,0.00001445923,0.001475446,0.0001290177,0.03601915],"genre_scores_gemma":[0.3096273,0.2503524,0.002363727,0.181657,0.1118347,0.0002016997,0.001725724,0.0007498527,0.1414877],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9966834,"threshold_uncertainty_score":0.2257361,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2969619689","doi":"10.1111/rssa.12497","title":"Regression-With-Residuals Estimation of Marginal Effects: A Method of Adjusting for Treatment-Induced Confounders That may also be Effect Modifiers","year":2019,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":25,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Marginal structural model; Confounding; Spurious relationship; Statistics; Marginal model; Econometrics; Regression; Mathematics; Set (abstract data type); Regression analysis; Point estimation; Estimation; Computer science; Engineering","authors":[{"name":"Geoffrey T. Wodtke","is_ca":false},{"name":"Zahide Alaca","is_ca":true},{"name":"Xiang Zhou","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06958519297076769,"gpt":0.4071576483818013,"spread":0.3375724554110336,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03763601,0.001412167,0.002392486,0.0020038,0.0005940665,0.001515317,0.003463513,0.001430759,0.006804534],"category_scores_gemma":[0.1214899,0.0008845605,0.003666385,0.002936315,0.002362848,0.002497647,0.002555975,0.00420065,0.00126907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001075592,"about_ca_system_score_gemma":0.003407386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006668489,"about_ca_topic_score_gemma":0.004695935,"domain_scores_codex":[0.9717017,0.02360767,0.0007341678,0.002103938,0.001558377,0.0002940938],"domain_scores_gemma":[0.9364921,0.04841408,0.002926473,0.01014367,0.001804978,0.0002187078],"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":[0.0003203874,0.000145621,0.007835343,0.0007741115,0.002160876,0.0002445316,0.0008152616,0.1022174,0.002123365,0.5149935,0.008046959,0.3603226],"study_design_scores_gemma":[0.000170701,0.0002693931,0.003069668,0.000259718,0.0005300419,0.0002152926,0.0001095544,0.4759088,0.002759992,0.4944214,0.0221831,0.0001023833],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001149576,0.0001412519,0.9979171,0.0001229114,0.00003619941,0.00006452788,0.00005731287,0.0002113062,0.0002997772],"genre_scores_gemma":[0.07248865,0.0004191026,0.9239694,0.0002230937,0.0001096839,0.0006514823,0.000274366,0.000365889,0.001498248],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03763601,"threshold_uncertainty_score":0.1990407,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2552583675","doi":"10.1111/rssa.12251","title":"Forecasting Daily Political Opinion Polls Using the Fractionally Cointegrated Vector Auto-Regressive Model","year":2016,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"Social Sciences and Humanities Research Council of Canada; Canada Research Chairs; Danmarks Grundforskningsfond; National Research Foundation","keywords":"Econometrics; Autoregressive model; Vector autoregression; Statistics; Economics; Mathematics","authors":[{"name":"Morten Ørregaard Nielsen","is_ca":true},{"name":"Sergei S. Shibaev","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02424294465825327,"gpt":0.2590347239243462,"spread":0.234791779266093,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002895273,0.0003750497,0.0006629472,0.0009786834,0.0001979457,0.001148405,0.0006079731,0.0006750263,0.001649775],"category_scores_gemma":[0.008980428,0.0002239331,0.0007118064,0.001023214,0.0002504522,0.001011817,0.000351356,0.0007767377,0.0004005356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005400522,"about_ca_system_score_gemma":0.0003641972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02902869,"about_ca_topic_score_gemma":0.0195471,"domain_scores_codex":[0.9994375,0.0002478477,0.00003552406,0.0001200264,0.00007971173,0.00007939915],"domain_scores_gemma":[0.9960374,0.002675483,0.0004894701,0.0002758731,0.0004188161,0.0001030266],"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":[0.0002767319,0.00007893668,0.0638919,0.00008107415,0.0001876758,0.0001389146,0.0001474242,0.8940982,0.001142576,0.004970557,0.001918711,0.03306726],"study_design_scores_gemma":[0.000005487977,0.00002839323,0.005390052,0.000005783131,0.00001089082,0.000006797668,0.00002351467,0.9932903,0.00014963,0.0008147744,0.0002662076,0.000008183772],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9667203,0.0004453125,0.02966722,0.0005597746,0.00008645465,0.00001151147,0.0006027653,0.0002080931,0.001698725],"genre_scores_gemma":[0.9968321,0.00009157637,0.001944483,0.0000221255,0.00002655359,0.000004338724,0.0005404148,0.000009454331,0.00052905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02902869,"threshold_uncertainty_score":0.05771941,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2487468973","doi":"10.1111/rssa.12324","title":"Differentially Private Model Selection with Penalized and Constrained Likelihood","year":2017,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":24,"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":"Differential privacy; Computer science; Inference; Statistical inference; Selection (genetic algorithm); Model selection; Population; Regularization (linguistics); Coding (social sciences); Data mining; Machine learning; Artificial intelligence; Mathematics; Statistics","authors":[{"name":"Jing Lei","is_ca":false},{"name":"Anne-Sophie Charest","is_ca":true},{"name":"Aleksandra Slavković","is_ca":false},{"name":"Adam Smith","is_ca":false},{"name":"Stephen E. Fienberg","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01537923605398333,"gpt":0.2614034817918333,"spread":0.24602424573785,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01464686,0.0009951583,0.001943201,0.001175879,0.0008218369,0.001924378,0.002666508,0.002093396,0.002386324],"category_scores_gemma":[0.05136199,0.000822872,0.001506058,0.00167361,0.003230066,0.003071188,0.003668342,0.003402478,0.0005166708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00204045,"about_ca_system_score_gemma":0.002205492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002290216,"about_ca_topic_score_gemma":0.001735527,"domain_scores_codex":[0.9864542,0.01032734,0.00035115,0.001065865,0.001450908,0.0003505646],"domain_scores_gemma":[0.9556217,0.03588835,0.001760259,0.004902165,0.001361985,0.0004654737],"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":[0.0002959733,0.0001138858,0.001416265,0.0001131119,0.0001447486,0.0003138547,0.0001535003,0.7480475,0.001102505,0.2034442,0.002068907,0.04278554],"study_design_scores_gemma":[0.00003069844,0.00002867326,0.000127498,0.000010862,0.00001033804,0.00004267771,0.000008016625,0.9201321,0.0004232145,0.07877628,0.0003937625,0.00001583171],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007561716,0.0001548998,0.990962,0.0005182638,0.00001707043,0.00004172549,0.00006020228,0.0001580696,0.0005260251],"genre_scores_gemma":[0.5508351,0.0004258011,0.4429925,0.0005794828,0.0001786163,0.0003976537,0.0004545013,0.000207993,0.003928281],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01464686,"threshold_uncertainty_score":0.07746089,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2113529524","doi":"10.1111/j.1467-985x.2010.00640.x","title":"Cultural Imagery and Statistical Models of the Force of Mortality: Addison, Gompertz and Pearson","year":2010,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Census and Population Estimation","field":"Mathematics","cited_by":20,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; University College London","keywords":"Gompertz function; Bridge (graph theory); Relation (database); History; Mathematics; Statistics; Computer science; Medicine","authors":[{"name":"Elizabeth L. Turner","is_ca":false},{"name":"James A. Hanley","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0321700090927592,"gpt":0.3175518253090399,"spread":0.2853818162162807,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002953983,0.0006206973,0.0003970062,0.002437314,0.0005911469,0.002369526,0.0006361136,0.0008851109,0.002416973],"category_scores_gemma":[0.01425109,0.0002801549,0.0003857709,0.001949041,0.004565319,0.003336676,0.0009654823,0.002631108,0.0004887978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002032528,"about_ca_system_score_gemma":0.0007106176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006765767,"about_ca_topic_score_gemma":0.003250535,"domain_scores_codex":[0.9990485,0.0006210951,0.00003709118,0.00008368245,0.000182219,0.00002741706],"domain_scores_gemma":[0.9922928,0.006221932,0.0003012794,0.0004419692,0.0006168508,0.0001251647],"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":[0.00001214264,0.00001315526,0.0007115367,0.00006059816,0.00001795895,0.00007580306,0.001357767,0.005072284,0.00004215323,0.9368718,0.03685884,0.01890582],"study_design_scores_gemma":[0.000006707376,0.00001597296,0.001478563,0.000173746,0.00001423181,0.0001711051,0.0005116981,0.01021928,0.00008399839,0.8910734,0.09622194,0.00002932269],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.05063115,0.1484926,0.1879521,0.3477242,0.004079833,0.00006144989,0.0008083451,0.0004688155,0.2597815],"genre_scores_gemma":[0.8114923,0.07769809,0.04260569,0.01403872,0.01127088,0.0001435405,0.0003674998,0.0002142299,0.04216909],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006765767,"threshold_uncertainty_score":0.01562232,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2946357294","doi":"10.1111/rssa.12473","title":"A Bayesian Approach to Developing a Stochastic Mortality Model for China","year":2019,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","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 Waterloo","funders":"","keywords":"Computer science; Bayesian probability; Econometrics; Stochastic modelling; Range (aeronautics); Set (abstract data type); Statistics; Mathematics; Artificial intelligence","authors":[{"name":"Johnny Siu-Hang Li","is_ca":true},{"name":"Kenneth Q. Zhou","is_ca":true},{"name":"Xiaobai Zhu","is_ca":true},{"name":"Wai‐Sum Chan","is_ca":false},{"name":"F Chan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02336082914448603,"gpt":0.3081380142899892,"spread":0.2847771851455032,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003150401,0.0005531737,0.0007312354,0.001243932,0.0004383921,0.0009887264,0.00158013,0.001137003,0.002615891],"category_scores_gemma":[0.005718831,0.0006593041,0.001132171,0.00124954,0.0006938534,0.0008846384,0.00124242,0.001079326,0.0003447431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001828784,"about_ca_system_score_gemma":0.002833051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03900383,"about_ca_topic_score_gemma":0.02582569,"domain_scores_codex":[0.9992929,0.0003436165,0.00003980359,0.0001143136,0.0001460018,0.00006334565],"domain_scores_gemma":[0.9985303,0.0009205696,0.000191716,0.00004697146,0.0002481572,0.00006226067],"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":[0.00000861767,0.000008825398,0.0007473615,0.00001848635,0.00001858219,0.00005751009,0.00004375872,0.9605996,0.0001598945,0.03318706,0.0004936235,0.00465667],"study_design_scores_gemma":[0.000003061177,0.000004775251,0.0001725032,0.000005115246,0.000004413724,0.000008030283,0.000006779173,0.9883814,0.00003124093,0.01097672,0.0003995488,0.000006476534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03112523,0.0002952849,0.9634258,0.0008068825,0.00003027999,0.00005936675,0.000559644,0.0001253893,0.003572145],"genre_scores_gemma":[0.7166187,0.001334426,0.2671444,0.000310056,0.0001785519,0.0007425368,0.001746854,0.0001351151,0.01178932],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03900383,"threshold_uncertainty_score":0.07755357,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2069182847","doi":"10.1111/1467-985x.00213","title":"A Simple Method for Estimating a Regression Model for κ Between a Pair of Raters","year":2001,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Cancer Care Ontario","funders":"National Institute of Mental Health; National Institutes of Health","keywords":"Multinomial logistic regression; Covariate; Logistic regression; Statistics; Linear regression; Econometrics; Function (biology); Psychology; Mathematics; Panel data; Social psychology","authors":[{"name":"Stuart R. Lipsitz","is_ca":false},{"name":"John Williamson","is_ca":false},{"name":"Neil Klar","is_ca":true},{"name":"Joseph G. Ibrahim","is_ca":false},{"name":"Michael Parzen","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07857670896700181,"gpt":0.4131196048038216,"spread":0.3345428958368198,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1291834,0.003471727,0.003630353,0.005124915,0.001707735,0.003487651,0.007041306,0.004011423,0.03031709],"category_scores_gemma":[0.3099272,0.002855897,0.007375321,0.005922122,0.002186582,0.004330104,0.004179919,0.008856873,0.01689273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002537094,"about_ca_system_score_gemma":0.003477505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009555454,"about_ca_topic_score_gemma":0.006540071,"domain_scores_codex":[0.8272325,0.1328546,0.00935248,0.01931835,0.009826622,0.001415389],"domain_scores_gemma":[0.7256327,0.2072499,0.01171811,0.04006682,0.01452618,0.0008062999],"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":[0.001607318,0.0005541118,0.0262988,0.001689611,0.005904063,0.0004960517,0.002785509,0.05448016,0.003078369,0.1050001,0.0564792,0.7416268],"study_design_scores_gemma":[0.001240382,0.001944925,0.03402644,0.001454923,0.001702904,0.001501227,0.001178412,0.5747531,0.008342549,0.2216892,0.1511293,0.001036592],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002032869,0.00008142384,0.9930754,0.0001768856,0.0001798242,0.001037698,0.0009452373,0.001677104,0.0007935348],"genre_scores_gemma":[0.03616379,0.00009091986,0.9497603,0.0001763257,0.0001169433,0.007464194,0.001401519,0.0008381896,0.003987777],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1291834,"threshold_uncertainty_score":0.683195,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2509064919","doi":"10.1111/rssa.12225","title":"The Dynamics of Adolescent Depression: An Instrumental Variable Quantile Regression with Fixed Effects Approach","year":2016,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Global Health Care Issues","field":"Health Professions","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"University of Melbourne","keywords":"Quantile regression; Instrumental variable; Econometrics; Quantile; Estimator; Fixed effects model; Regression; Regression analysis; Statistics; Multilevel model; Psychology; Mathematics; Panel data","authors":[{"name":"Paul Contoyannis","is_ca":true},{"name":"Jinhu Li","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01507905506796272,"gpt":0.3382337958990931,"spread":0.3231547408311304,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00901725,0.0004294991,0.001313786,0.001454313,0.000367594,0.001432876,0.003148708,0.0008974078,0.003300676],"category_scores_gemma":[0.02959639,0.0006612726,0.001528854,0.001806126,0.0009517342,0.001162514,0.001737587,0.00201828,0.0003389622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009661876,"about_ca_system_score_gemma":0.00171401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01418914,"about_ca_topic_score_gemma":0.007356975,"domain_scores_codex":[0.9964348,0.002575101,0.0001060848,0.0003857702,0.0002566193,0.0002417304],"domain_scores_gemma":[0.9862195,0.01036932,0.001354809,0.00119577,0.0006759134,0.0001847626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00009710428,0.0001482006,0.06366852,0.0001551308,0.0009003219,0.0005411911,0.0003992671,0.562668,0.0005397873,0.3149222,0.00332461,0.0526357],"study_design_scores_gemma":[0.00002633394,0.00003226466,0.005311538,0.0000526022,0.0001008631,0.00004216778,0.00007501306,0.9313404,0.0002294216,0.06059526,0.002162794,0.00003135024],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05163434,0.000427928,0.9441193,0.0009222984,0.00005810777,0.00007915223,0.0004760443,0.0001749964,0.002107739],"genre_scores_gemma":[0.8626038,0.001026399,0.1278135,0.0002888271,0.0001809318,0.0003265176,0.001030454,0.0001182292,0.006611409],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01418914,"threshold_uncertainty_score":0.04768831,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4317892506","doi":"10.1093/jrsssa/qnac010","title":"Multivariate claim count regression model with varying dispersion and dependence parameters","year":2023,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Overdispersion; Poisson regression; Multivariate statistics; Econometrics; Statistics; Mathematics; Dispersion (optics); Count data; Bivariate analysis; Poisson distribution; Regression; Population","authors":[{"name":"Himchan Jeong","is_ca":true},{"name":"George Tzougas","is_ca":false},{"name":"Tsz Chai Fung","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04626687223989741,"gpt":0.3391948264382115,"spread":0.2929279541983141,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01788349,0.001358642,0.002462712,0.002440128,0.0006339393,0.002243354,0.004979996,0.003217946,0.004141863],"category_scores_gemma":[0.03707451,0.001081365,0.001825586,0.00354163,0.002069735,0.003191381,0.001980569,0.004159498,0.0009046148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002049968,"about_ca_system_score_gemma":0.001075714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0142966,"about_ca_topic_score_gemma":0.006352984,"domain_scores_codex":[0.9935344,0.003851164,0.0002871993,0.001241486,0.0006997109,0.0003859274],"domain_scores_gemma":[0.9624558,0.02843903,0.004584314,0.002311875,0.00179882,0.0004102091],"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":[0.0004471943,0.0002761364,0.0167984,0.0001639269,0.0003004284,0.0006771909,0.0005331141,0.7512937,0.002402964,0.196644,0.001989692,0.02847326],"study_design_scores_gemma":[0.00003351905,0.00003678031,0.002023964,0.0000191772,0.00003744851,0.00007966009,0.00002859701,0.9743988,0.0002048864,0.0226697,0.0004369232,0.00003058523],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1731788,0.0004684162,0.8206929,0.001592209,0.0000429501,0.0001409084,0.001296623,0.0006814435,0.001905799],"genre_scores_gemma":[0.9004822,0.0005256853,0.08796317,0.0002306498,0.000140863,0.0004173595,0.00156365,0.0001726173,0.008503681],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01788349,"threshold_uncertainty_score":0.09457809,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3154947088","doi":"10.1111/rssa.12678","title":"Modified Poisson Regression Analysis of Grouped and Right-Censored Counts","year":2021,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Research Grants Council, University Grants Committee","keywords":"Poisson regression; Censoring (clinical trials); Estimator; Poisson distribution; Statistics; Logistic regression; Econometrics; Inference; Statistical inference; Mathematics; Sample (material); Computer science; Psychology; Demography; Sociology; Artificial intelligence; Population","authors":[{"name":"Qiang Fu","is_ca":true},{"name":"Tian-Yi Zhou","is_ca":false},{"name":"Xin Guo","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0364367142514604,"gpt":0.3332625916606636,"spread":0.2968258774092032,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02296524,0.0007387629,0.001783923,0.00284997,0.0004831124,0.001331886,0.004901392,0.001393842,0.004723137],"category_scores_gemma":[0.1057278,0.0006793672,0.002168012,0.003638136,0.001857707,0.002736308,0.002244744,0.002035143,0.0008992438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001184747,"about_ca_system_score_gemma":0.001078112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004784232,"about_ca_topic_score_gemma":0.002637889,"domain_scores_codex":[0.9816955,0.01383049,0.0005680858,0.001669324,0.001790335,0.0004463147],"domain_scores_gemma":[0.9123297,0.06728059,0.006999478,0.008372805,0.004378361,0.0006390978],"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":[0.0003986265,0.0001849921,0.0257683,0.000775402,0.0006685167,0.0009468165,0.0009854996,0.4263248,0.002496172,0.390646,0.004069245,0.1467356],"study_design_scores_gemma":[0.00003380414,0.00008181069,0.003175262,0.00008123915,0.00005192492,0.0001797757,0.0001030672,0.9103381,0.0005496389,0.08350979,0.001853759,0.0000418744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02806888,0.0003124867,0.9702182,0.0001767681,0.00006213921,0.0001027549,0.0001988223,0.000229958,0.0006299157],"genre_scores_gemma":[0.6041743,0.0005621279,0.3886024,0.0002436439,0.0001906717,0.0006689815,0.000843701,0.0002369892,0.004477202],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02296524,"threshold_uncertainty_score":0.1214532,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4391116419","doi":"10.1093/jrsssa/qnae002","title":"Grace periods in comparative effectiveness studies of sustained treatments","year":2024,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institutes of Health; Kaiser Permanente","keywords":"Environmental science","authors":[{"name":"Kerollos Nashat Wanis","is_ca":false},{"name":"Aaron L. Sarvet","is_ca":false},{"name":"Lan Wen","is_ca":true},{"name":"Jason P. Block","is_ca":false},{"name":"Sheryl L. Rifas‐Shiman","is_ca":false},{"name":"James M. Robins","is_ca":false},{"name":"Jessica G. Young","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2368553120899317,"gpt":0.4700912487190809,"spread":0.2332359366291491,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2591486,0.001611839,0.004962702,0.003481586,0.0006199544,0.003494588,0.002575062,0.00387856,0.00564513],"category_scores_gemma":[0.4507875,0.001124575,0.007380221,0.00330193,0.004252872,0.005428207,0.003534761,0.004574968,0.0002634683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003287644,"about_ca_system_score_gemma":0.003331591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001948335,"about_ca_topic_score_gemma":0.0009469584,"domain_scores_codex":[0.7129841,0.2632156,0.008442165,0.00558551,0.007802519,0.001970182],"domain_scores_gemma":[0.4018826,0.5470772,0.02891888,0.01795554,0.002765633,0.001400214],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.02383652,0.0008685744,0.0298177,0.008801751,0.03284189,0.0004232811,0.00155597,0.2285338,0.0008488938,0.4846766,0.004057619,0.1837375],"study_design_scores_gemma":[0.005849598,0.01364422,0.02760022,0.00468792,0.01390757,0.0004147683,0.0006587026,0.3386879,0.002067124,0.5762607,0.01574857,0.0004727446],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1760138,0.05871196,0.7321494,0.008261473,0.001859407,0.004466103,0.00208319,0.0005618406,0.0158928],"genre_scores_gemma":[0.9168629,0.004360052,0.07009143,0.001564928,0.0006290307,0.003948309,0.0005537918,0.00009041911,0.001899165],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7408514,"threshold_uncertainty_score":0.9136016,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2151527082","doi":"10.1111/rssa.12161","title":"Healthcare Facility Choice and User Fee Abolition: Regression Discontinuity in a Multinomial Choice Setting","year":2016,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Center for High Performance Computing","keywords":"Multinomial logistic regression; Regression discontinuity design; Multinomial distribution; Health care; Regression; Discontinuity (linguistics); Econometrics; Computer science; Economics; Statistics; Mathematics","authors":[{"name":"Steven F. Koch","is_ca":false},{"name":"Jeffrey S. Racine","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02787460129028851,"gpt":0.2896143363312332,"spread":0.2617397350409447,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02375086,0.0003796722,0.001987278,0.001449437,0.0009151402,0.002460648,0.002781134,0.001528036,0.006975416],"category_scores_gemma":[0.06758505,0.0005555006,0.002769679,0.002611733,0.002194248,0.0019883,0.002567477,0.00395676,0.000393855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002023972,"about_ca_system_score_gemma":0.001068081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03656868,"about_ca_topic_score_gemma":0.01637352,"domain_scores_codex":[0.970752,0.02473222,0.0007965012,0.001158792,0.001035707,0.001524712],"domain_scores_gemma":[0.8664045,0.1108391,0.01515172,0.004824249,0.001503871,0.001276533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002452833,0.001082688,0.7136135,0.0005300146,0.002896346,0.001986172,0.002782864,0.1407645,0.000880503,0.09579395,0.002858766,0.03435789],"study_design_scores_gemma":[0.0005239856,0.00118276,0.3433133,0.0002737876,0.000919491,0.000697876,0.003672477,0.5917206,0.001320385,0.05152017,0.004615502,0.0002396974],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9567643,0.0007482073,0.03753075,0.001636585,0.00006744966,0.0001135507,0.0008304116,0.00006647973,0.00224221],"genre_scores_gemma":[0.9957469,0.00009521446,0.002914777,0.00008190805,0.00002196259,0.00005348953,0.0002140445,0.000008168116,0.0008634148],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03656868,"threshold_uncertainty_score":0.125608,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2033430493","doi":"10.1111/j.1467-985x.2005.00393.x","title":"Editorial: (Post-normal) Statistical Science","year":2005,"lang":"en","type":"editorial","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Statistics Education and Methodologies","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Statistics; Psychology; Mathematics; Econometrics; Mathematics education","authors":[{"name":"James V. Zidek","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03295820726418767,"gpt":0.3767539915515631,"spread":0.3437957842873754,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.012615,0.005124451,0.006648248,0.01040682,0.003952756,0.01023996,0.004349473,0.01465295,0.02154324],"category_scores_gemma":[0.06130558,0.001707384,0.004401396,0.004201155,0.004878481,0.004265688,0.001803226,0.01857704,0.0192902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004163211,"about_ca_system_score_gemma":0.003975339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002237058,"about_ca_topic_score_gemma":0.006571084,"domain_scores_codex":[0.9889868,0.001898831,0.001959955,0.001488043,0.005055373,0.0006110444],"domain_scores_gemma":[0.9351634,0.02135142,0.003769057,0.002532005,0.03105689,0.006127137],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002294314,0.000008149722,0.00001812649,0.00009880807,0.00001759727,0.00007071043,0.000004693105,0.00002305632,0.0000294091,0.0001284289,0.9969765,0.002601527],"study_design_scores_gemma":[0.000104803,0.00004712092,0.0007475152,0.0004135074,0.0001133894,0.0004367632,0.00003855394,0.0003905551,0.0001831853,0.001852273,0.9956321,0.00004013581],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00001427154,0.001167238,0.0001474079,0.009931024,0.9882544,0.000008855643,0.00003719213,0.0000541733,0.0003854701],"genre_scores_gemma":[0.0003621865,0.001287047,0.000185922,0.008657592,0.9836969,0.00002429624,0.00004068622,0.00005930716,0.005686102],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.987385,"threshold_uncertainty_score":0.07206929,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2137001680","doi":"10.1111/1467-985x.00271","title":"Tobacco: Public Perceptions and the Role of the Industry","year":2003,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Smoking Behavior and Cessation","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Tobacco control; Legislation; Tobacco industry; Promotion (chess); Control (management); Public health; Perception; Health promotion; Business; European union; Public policy; Public relations; Political science; Environmental health; Medicine; Psychology; Economics; Law; Politics; Economic policy; Nursing; Management","authors":[{"name":"David Simpson","is_ca":false},{"name":"Sue Lee","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0143768977938832,"gpt":0.2723193362981619,"spread":0.2579424385042787,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003467937,0.0001449362,0.0001921804,0.0009789487,0.00115276,0.005575152,0.000341953,0.001800557,0.006588829],"category_scores_gemma":[0.004858312,0.0001023011,0.0002104791,0.0008134576,0.003429762,0.003273606,0.002276661,0.002095808,0.0004271222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001836355,"about_ca_system_score_gemma":0.001379753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005256061,"about_ca_topic_score_gemma":0.005115455,"domain_scores_codex":[0.9973273,0.00107287,0.0000877811,0.0001233239,0.001003833,0.0003849377],"domain_scores_gemma":[0.9943367,0.002905345,0.001131632,0.0001914452,0.0008167166,0.0006181691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003113235,0.0006097428,0.2835531,0.001467114,0.00008861528,0.001556947,0.1544194,0.0008722242,0.003803979,0.2535195,0.05939564,0.2404024],"study_design_scores_gemma":[0.00002085467,0.0005335602,0.2525727,0.001224545,0.0000723153,0.001140274,0.2807792,0.0009853219,0.0009058221,0.04940458,0.4122745,0.00008634109],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5724632,0.02038555,0.0008888303,0.1903454,0.001102703,0.00002644616,0.0001880519,0.000045097,0.2145548],"genre_scores_gemma":[0.9893137,0.003261348,0.00006118459,0.003486516,0.0003967532,0.000004648186,0.00003324931,0.000007627616,0.003434959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006588829,"threshold_uncertainty_score":0.0220418,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3194224122","doi":"10.1111/rssa.12745","title":"Machine Learning Approaches to Identify Thresholds in a Heat-Health Warning System Context","year":2021,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ouranos; University of Ottawa; Health Canada; Institut National de Santé Publique du Québec; Institut National de la Recherche Scientifique","funders":"","keywords":"Context (archaeology); Benchmark (surveying); Regression; Multivariate statistics; Warning system; Multivariate adaptive regression splines; Regression analysis; Function (biology)","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.08845564951827194,"gpt":0.3188602847187995,"spread":0.2304046352005275,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007226638,0.0006290726,0.0008751841,0.002461195,0.0003923921,0.001451992,0.001201994,0.001052578,0.001793695],"category_scores_gemma":[0.01932179,0.000238754,0.0006617183,0.001702661,0.0005867184,0.001218825,0.001287707,0.001874196,0.0002118981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009625609,"about_ca_system_score_gemma":0.001008312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003869823,"about_ca_topic_score_gemma":0.003735778,"domain_scores_codex":[0.9969077,0.002146669,0.0001842604,0.0003638751,0.0002456738,0.0001519766],"domain_scores_gemma":[0.9822964,0.01505816,0.001055764,0.0003861039,0.0009344401,0.0002691162],"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":[0.0002352877,0.0003148272,0.04843973,0.0003115541,0.0003918853,0.0002472266,0.0003133072,0.7858898,0.000682924,0.02697399,0.003049219,0.1331503],"study_design_scores_gemma":[0.000007507808,0.00004427725,0.003014573,0.00002902719,0.00001512846,0.00001826256,0.00007474051,0.9753283,0.0001718411,0.02088164,0.0004056185,0.000009019068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2434625,0.002075286,0.7467959,0.002281925,0.0001691235,0.0001571968,0.0007520392,0.0004256549,0.003880441],"genre_scores_gemma":[0.9235687,0.0002997023,0.07481637,0.0001234799,0.000108944,0.00009589874,0.0003974739,0.0000207523,0.0005686727],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007226638,"threshold_uncertainty_score":0.03821856,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2747702080","doi":"10.1111/rssa.12308","title":"Clustering in Small Area Estimation with Area Level Linear Mixed Models","year":2017,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cluster analysis; Estimator; Small area estimation; Statistics; Variance (accounting); Homogeneity (statistics); Mean squared error; Mathematics; Euclidean distance; Computer science; Artificial intelligence","authors":[{"name":"Elaheh Torkashvand","is_ca":true},{"name":"Mohammad Jafari Jozani","is_ca":true},{"name":"Mahmoud Torabi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.127003631371638,"gpt":0.3472797529928348,"spread":0.2202761216211968,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01903442,0.001021525,0.001921887,0.002341194,0.0008337772,0.001836109,0.002642033,0.00150157,0.001571356],"category_scores_gemma":[0.0631657,0.0008083689,0.001759042,0.002501845,0.001734275,0.001867089,0.002245627,0.002021321,0.0002923735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001488014,"about_ca_system_score_gemma":0.001306486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008094607,"about_ca_topic_score_gemma":0.007880937,"domain_scores_codex":[0.9838296,0.01335804,0.0003658888,0.001606419,0.0005939823,0.0002460501],"domain_scores_gemma":[0.9321323,0.05835122,0.004000193,0.003063534,0.002086052,0.0003667605],"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":[0.0002904943,0.00009979782,0.02322206,0.0002923084,0.0009174691,0.0002015009,0.000427576,0.8409321,0.0006679887,0.06848974,0.001470185,0.0629888],"study_design_scores_gemma":[0.00001473498,0.00004596664,0.001661712,0.00002400844,0.0000437113,0.0000188256,0.0000433329,0.9568494,0.0002232741,0.04054927,0.0005071758,0.00001853163],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0281258,0.0003652151,0.9705493,0.0002452268,0.0000279799,0.00006810546,0.0001016159,0.0001422067,0.0003745958],"genre_scores_gemma":[0.5471112,0.0004459936,0.4494632,0.0001857416,0.0001272229,0.0004767937,0.000595641,0.0001007836,0.001493427],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01903442,"threshold_uncertainty_score":0.1006648,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3209944773","doi":"10.1111/rssa.12716","title":"Propensity Score Analysis for a Semi-Continuous Exposure Variable: A Study of Gestational Alcohol Exposure and Childhood Cognition","year":2021,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Natural Sciences and Engineering Research Council of Canada","keywords":"Propensity score matching; Covariate; Statistics; Observational study; Econometrics; Instrumental variable; Regression analysis; Regression; Linear regression; Mathematics","authors":[{"name":"Tuğba Akkaya Hocagil","is_ca":true},{"name":"Richard J. Cook","is_ca":true},{"name":"Sandra W. Jacobson","is_ca":false},{"name":"Joseph L. Jacobson","is_ca":false},{"name":"Louise Ryan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06640264768141525,"gpt":0.3327083456366718,"spread":0.2663056979552566,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00713336,0.0003572605,0.000540235,0.0009356822,0.0005063272,0.0007922408,0.0007225513,0.0008429744,0.002053983],"category_scores_gemma":[0.02808983,0.0002026491,0.001922892,0.001750029,0.001028936,0.0007591632,0.001332805,0.001597507,0.0001801695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005990906,"about_ca_system_score_gemma":0.001526372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009843091,"about_ca_topic_score_gemma":0.005713717,"domain_scores_codex":[0.997122,0.001999064,0.0001058527,0.0003623655,0.000313871,0.00009668694],"domain_scores_gemma":[0.9859027,0.009175418,0.002067094,0.001907408,0.0005073452,0.0004400325],"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":[0.002157771,0.0006515538,0.8038538,0.0004421132,0.00405772,0.001278938,0.001388664,0.02597393,0.001838725,0.04516862,0.002732889,0.1104553],"study_design_scores_gemma":[0.0005531252,0.001606286,0.7290152,0.0003571731,0.002013529,0.001571806,0.001103109,0.1788086,0.001483252,0.07667889,0.006689203,0.0001198046],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9166641,0.002589223,0.07605793,0.002530924,0.00008163822,0.00009432111,0.0004971911,0.00005791116,0.001426831],"genre_scores_gemma":[0.9839175,0.0007823132,0.01418589,0.0001849871,0.00005094035,0.00006899826,0.0002086235,0.00001521753,0.0005855791],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.009843091,"threshold_uncertainty_score":0.03772527,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3007882062","doi":"10.1111/rssa.12551","title":"Spatial Confounding in Hurdle Multilevel Beta Models: the Case of the Brazilian Mathematical Olympics for Public Schools","year":2020,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Multilevel model; Random effects model; Mathematics education; Distribution (mathematics); Fixed effects model; Confounding; Complement (music); Psychology; Econometrics; Statistics; Mathematics; Medicine; Panel data","authors":[{"name":"João Batista Pereira","is_ca":false},{"name":"Widemberg S. Nobre","is_ca":false},{"name":"Igor F. L. Silva","is_ca":false},{"name":"Alexandra M. Schmidt","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07025332993555793,"gpt":0.2704118587743717,"spread":0.2001585288388138,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02430211,0.0009778882,0.002261115,0.001453386,0.001723887,0.002435428,0.003449369,0.001992712,0.005319855],"category_scores_gemma":[0.0491087,0.0009060873,0.003339569,0.002188082,0.002771647,0.002037517,0.003706987,0.003627382,0.0005014514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001625239,"about_ca_system_score_gemma":0.001944812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09558578,"about_ca_topic_score_gemma":0.06588473,"domain_scores_codex":[0.9882082,0.008053333,0.0002916651,0.001949488,0.000441198,0.001056155],"domain_scores_gemma":[0.9287481,0.05151867,0.00910602,0.006564277,0.002482856,0.001580075],"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":[0.0007178671,0.0003385445,0.4836354,0.0003176877,0.002457615,0.002458376,0.00418204,0.1604711,0.0006060239,0.2962669,0.008799653,0.03974872],"study_design_scores_gemma":[0.0002257527,0.0003067736,0.0944692,0.00028147,0.0008624884,0.0004760707,0.002631037,0.7176731,0.0003669892,0.1753521,0.007197275,0.0001576636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8297848,0.001971652,0.1529452,0.007714024,0.0001520923,0.0001734985,0.001877683,0.0002688825,0.005112135],"genre_scores_gemma":[0.9851155,0.000373883,0.01110905,0.0002511974,0.00008152621,0.0001280417,0.0005945299,0.00004335956,0.002302983],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.09558578,"threshold_uncertainty_score":0.1900588,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2009786076","doi":"10.1046/j.0964-1998.2003.00636.x","title":"Evaluation of Adjustments for Partial Non-Response Bias in the US National Immunization Survey","year":2003,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Non-response bias; Respondent; Ask price; Weighting; Statistics; Missing data; Outcome (game theory); Medicine; Psychology; Econometrics; Actuarial science; Mathematics; Economics","authors":[{"name":"Philip Smith","is_ca":false},{"name":"David C. Hoaglin","is_ca":false},{"name":"J. N. K. Rao","is_ca":true},{"name":"Danni Daniels","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.085675468358582,"gpt":0.3761607813917029,"spread":0.290485313033121,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.4004529,0.002201781,0.002877963,0.004099743,0.001147045,0.002419676,0.005275926,0.001999924,0.005765219],"category_scores_gemma":[0.7263805,0.001290106,0.007749242,0.007353118,0.002657089,0.003943515,0.004674233,0.002173938,0.0004761134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002522901,"about_ca_system_score_gemma":0.003440019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004842472,"about_ca_topic_score_gemma":0.002996007,"domain_scores_codex":[0.4002489,0.553983,0.01828883,0.007520371,0.0178023,0.002156571],"domain_scores_gemma":[0.1777336,0.7556625,0.02621692,0.02558607,0.01384016,0.0009606954],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01799357,0.0004931805,0.2043018,0.008677242,0.04792155,0.0004879744,0.004335218,0.05603641,0.0009130774,0.03210412,0.009723938,0.617012],"study_design_scores_gemma":[0.007103016,0.0304247,0.4000652,0.005788686,0.05815084,0.001740792,0.004569288,0.3320053,0.008581259,0.06678102,0.08349805,0.001291859],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2505127,0.01454686,0.6916077,0.007774896,0.002391638,0.01668548,0.004103106,0.002601877,0.009775849],"genre_scores_gemma":[0.7384501,0.001197939,0.2510049,0.0007756522,0.0003621505,0.005603633,0.001008554,0.0003427362,0.001254259],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5995471,"threshold_uncertainty_score":0.7393484,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1945845966","doi":"10.1111/j.1467-985x.2009.00628.x","title":"Staying Together for the Sake of the Home?: House Price Shocks and Partnership Dissolution in the UK","year":2010,"lang":"en","type":"preprint","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Family Dynamics and Relationships","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Economic and Social Research Council; University of Essex","keywords":"House price; General partnership; British Household Panel Survey; Economics; Price shock; Debt; Monetary economics; Labour economics; Demographic economics; Finance","authors":[{"name":"Helmut Rainer","is_ca":false},{"name":"Ian Smith","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.031839605142196,"gpt":0.3099365150956543,"spread":0.2780969099534584,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009259061,0.0001504298,0.000450796,0.000909195,0.0005189239,0.001505502,0.0003563965,0.0004398561,0.004433344],"category_scores_gemma":[0.007191663,0.0001873576,0.0002845228,0.002307108,0.0005853226,0.0009615518,0.001860519,0.0009653373,0.0004003372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001245748,"about_ca_system_score_gemma":0.0005697205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09813624,"about_ca_topic_score_gemma":0.08977702,"domain_scores_codex":[0.9990425,0.000323715,0.0001365628,0.0001201243,0.0002059951,0.0001710431],"domain_scores_gemma":[0.9927465,0.002244226,0.003333229,0.0003788205,0.0005497049,0.0007475149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001559926,0.00003477294,0.9854951,0.00004163578,0.00009456331,0.0003274748,0.001833644,0.0007850137,0.0001012493,0.0009066242,0.001380435,0.008843496],"study_design_scores_gemma":[0.000006956666,0.00004250763,0.9930808,0.00003914832,0.00002035881,0.0001444353,0.003944854,0.0008225213,0.00007810159,0.0005552244,0.00125047,0.00001472051],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961841,0.0006620715,0.0001936278,0.0008702499,0.0000132759,0.000006103442,0.001011845,0.000002018522,0.001056654],"genre_scores_gemma":[0.9987325,0.000324787,0.00003467214,0.00003889288,0.000007422398,0.000003918613,0.0003759369,0.000001403804,0.0004805468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09813624,"threshold_uncertainty_score":0.1951301,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2154106034","doi":"10.1111/rssa.12041","title":"Geostatistical Survival Models for Environmental Risk Assessment with Large Retrospective Cohorts","year":2013,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto; McMaster University; Cancer Care Ontario","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Laplace's method; Retrospective cohort study; Statistics; Markov random field; Computer science; Bayesian probability; Population; Inference; Bayesian inference; Cancer registry; Econometrics; Data mining; Medicine; Mathematics; Artificial intelligence; Environmental health","authors":[{"name":"Huan Jiang","is_ca":true},{"name":"Håvard Rue","is_ca":false},{"name":"Sílvia Emiko Shimakura","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06986250356708025,"gpt":0.3485283118975758,"spread":0.2786658083304956,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02411414,0.0008590802,0.001283729,0.002144018,0.0006227778,0.001477769,0.002489004,0.001425677,0.004392879],"category_scores_gemma":[0.04450762,0.001135864,0.002269686,0.002531432,0.001801571,0.001330944,0.002386223,0.00251647,0.0007440925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001514439,"about_ca_system_score_gemma":0.002106916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02148309,"about_ca_topic_score_gemma":0.01664793,"domain_scores_codex":[0.9939179,0.004414186,0.0002238223,0.0006646652,0.0005417622,0.0002376389],"domain_scores_gemma":[0.9536555,0.03844056,0.003378478,0.002570775,0.001486447,0.0004683072],"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":[0.0001089905,0.00006472506,0.01920832,0.00008969652,0.0003561872,0.0002766896,0.0002336737,0.8201954,0.0001901726,0.1328122,0.002783053,0.02368095],"study_design_scores_gemma":[0.00002639498,0.00003171869,0.001680407,0.00002999845,0.00003824169,0.00005567864,0.00004603761,0.9223182,0.00005374023,0.07395755,0.001743804,0.00001829433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02932093,0.0005433943,0.9663861,0.00116701,0.0000765903,0.0001727664,0.001127133,0.0002737484,0.0009323893],"genre_scores_gemma":[0.6577629,0.00187379,0.3228641,0.0006534752,0.0004327977,0.001986036,0.004044024,0.0002029765,0.01017984],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02411414,"threshold_uncertainty_score":0.1275293,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2164485036","doi":"10.1111/j.1467-985x.2012.01035.x","title":"Assessing the Accuracy of Non-Random Business Conditions Surveys: A Novel Approach","year":2012,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Bank of Canada","funders":"","keywords":"Stratified sampling; Sampling (signal processing); Sample (material); Econometrics; Sample size determination; Publication; Computer science; Dispersion (optics); Monte Carlo method; Cluster analysis; Sampling design; Selection (genetic algorithm); Statistics; Population; Survey sampling; Economics; Mathematics; Business; Machine learning","authors":[{"name":"Daniel de Munnik","is_ca":true},{"name":"Mark Illing","is_ca":true},{"name":"David Dupuis","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06736458653412752,"gpt":0.3295821754106591,"spread":0.2622175888765316,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.08526535,0.0008946761,0.002044753,0.006386278,0.001374899,0.005063615,0.003924558,0.003181611,0.001612578],"category_scores_gemma":[0.3684974,0.001024932,0.001626585,0.005702437,0.004457634,0.004917879,0.005793448,0.003148057,0.0004141218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003821048,"about_ca_system_score_gemma":0.002910503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005592579,"about_ca_topic_score_gemma":0.0034588,"domain_scores_codex":[0.8304996,0.1307241,0.006381512,0.01254303,0.01852648,0.0013253],"domain_scores_gemma":[0.4084333,0.4883013,0.04524094,0.04126663,0.01539925,0.001358668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004886033,0.0003992989,0.2531986,0.001049363,0.002130817,0.0007194129,0.003304509,0.1404448,0.001468071,0.2314232,0.006340293,0.3590331],"study_design_scores_gemma":[0.0001164793,0.000363677,0.04870169,0.0004323645,0.0002711195,0.000948076,0.001081036,0.6270678,0.001945973,0.3065372,0.01234185,0.0001926804],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05650997,0.0007429625,0.9358047,0.00219621,0.0001133588,0.0002878723,0.0005033204,0.0002509847,0.003590666],"genre_scores_gemma":[0.6855919,0.0003637249,0.3117481,0.0004269709,0.0003096532,0.0004014644,0.000505901,0.00005786126,0.0005944094],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08526535,"threshold_uncertainty_score":0.4509316,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2169504063","doi":"10.1111/j.1467-985x.2011.00695.x","title":"Modelling Member Behaviour in on-Line User-Generated Content Sites: A Semiparametric Bayesian Approach","year":2011,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"York University","keywords":"Bivariate analysis; Event (particle physics); User-generated content; Computer science; Econometrics; Set (abstract data type); Bayesian probability; Line (geometry); Linear model; Machine learning; Artificial intelligence; Social media; Mathematics; World Wide Web","authors":[{"name":"Young-Hoon Park","is_ca":false},{"name":"Chang Hee Park","is_ca":false},{"name":"Pulak Ghosh","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07675050356163719,"gpt":0.2859784746130932,"spread":0.209227971051456,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005802684,0.0006981894,0.00145046,0.001674792,0.0006000612,0.002098269,0.003513982,0.002604711,0.003922238],"category_scores_gemma":[0.02390215,0.001082541,0.001297304,0.001378323,0.001543504,0.003016096,0.00187166,0.002143822,0.0008774553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001671766,"about_ca_system_score_gemma":0.001016958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01988591,"about_ca_topic_score_gemma":0.01356787,"domain_scores_codex":[0.9979899,0.0011399,0.00005736824,0.0004016706,0.0002073673,0.0002038108],"domain_scores_gemma":[0.9835346,0.01226145,0.001988913,0.0008258556,0.0008248005,0.0005642773],"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":[0.000128985,0.0001486888,0.01643683,0.00005548908,0.0001433111,0.000182886,0.000491805,0.9092346,0.0007975037,0.05955631,0.001225062,0.01159865],"study_design_scores_gemma":[0.000006891861,0.00001555729,0.001152487,0.000005919646,0.00000920926,0.00002118118,0.00003582254,0.9863023,0.00004823526,0.01217913,0.0002126756,0.00001063505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.280998,0.0001694591,0.7141445,0.001013108,0.00002471078,0.0001240401,0.0006900005,0.0002363213,0.002599914],"genre_scores_gemma":[0.9404998,0.0002195998,0.05187974,0.0001202253,0.00005282259,0.0002529348,0.0006519672,0.00008443264,0.006238543],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01988591,"threshold_uncertainty_score":0.03954029,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1523682324","doi":"10.1111/j.1467-985x.2012.01037.x","title":"The Master of the Royal Mint: How Much Money did Isaac Newton Save Britain?","year":2012,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Historical Economic and Social Studies","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"British Columbia Institute of Technology","funders":"Smithsonian Libraries; Simon Fraser University; Smithsonian Institution","keywords":"Jury; Mathematics; Mathematical economics; Law; Political science","authors":[{"name":"Ari Belenkiy","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02327769989293297,"gpt":0.2140034611114706,"spread":0.1907257612185377,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006930564,0.0002945609,0.0007728813,0.001551911,0.002049354,0.004968531,0.0008717738,0.001573663,0.01031627],"category_scores_gemma":[0.05871984,0.0002871307,0.0002432572,0.0026939,0.006934976,0.004011528,0.001952602,0.003511565,0.001610211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007005059,"about_ca_system_score_gemma":0.003431895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02662138,"about_ca_topic_score_gemma":0.03083283,"domain_scores_codex":[0.9955971,0.001843866,0.0002273008,0.0005396076,0.001368808,0.0004234013],"domain_scores_gemma":[0.9819536,0.01033504,0.002856907,0.0009865044,0.002660944,0.001206997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0005453781,0.00003592959,0.01932,0.001047025,0.0002165821,0.0005385138,0.02006925,0.001550518,0.0002690062,0.2788374,0.4710235,0.2065469],"study_design_scores_gemma":[0.00002998375,0.0001755762,0.05924927,0.002897779,0.00007694763,0.0003764631,0.01076373,0.0007015963,0.0004148969,0.07107055,0.8541079,0.0001352943],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.129327,0.1617237,0.00326241,0.6035678,0.008028903,0.00002339676,0.001309228,0.0001033875,0.09265414],"genre_scores_gemma":[0.8484518,0.06259688,0.00152064,0.03578428,0.008516952,0.0000421217,0.0006192526,0.000187696,0.04228037],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02662138,"threshold_uncertainty_score":0.05293286,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4391754879","doi":"10.1093/jrsssa/qnae009","title":"The one-sayers model for the Extended Crosswise design","year":2024,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"World Anti-Doping Agency","keywords":"Randomized response; Test (biology); Logistic regression; Goodness of fit; Statistics; Response bias; Psychology; Randomization; Mathematics; Econometrics; Social psychology; Randomized controlled trial; Medicine","authors":[{"name":"Maarten Cruyff","is_ca":false},{"name":"Khadiga H. A. Sayed","is_ca":false},{"name":"Andrea Petróczi","is_ca":false},{"name":"P.G.M. van der Heijden","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1121720310689092,"gpt":0.3741153706668705,"spread":0.2619433395979613,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.2245589,0.003055287,0.005131659,0.003807192,0.002113142,0.004029214,0.005901427,0.007206874,0.0315718],"category_scores_gemma":[0.2449603,0.002040776,0.004470538,0.003047365,0.009736697,0.006438929,0.004324183,0.006774707,0.003750762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002553286,"about_ca_system_score_gemma":0.002609929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002302189,"about_ca_topic_score_gemma":0.001513319,"domain_scores_codex":[0.7393171,0.2314118,0.004175952,0.01464897,0.006514887,0.003931346],"domain_scores_gemma":[0.4778482,0.445567,0.03344484,0.03083258,0.009806951,0.002500458],"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":[0.007020745,0.001762083,0.04692701,0.001629905,0.002579216,0.001110803,0.00649807,0.116467,0.00162125,0.7150947,0.008349483,0.09093964],"study_design_scores_gemma":[0.002096147,0.005227681,0.008151793,0.0005292681,0.000656694,0.0004921064,0.001119449,0.6814302,0.001477911,0.2928142,0.005677707,0.0003269428],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1612214,0.0005417898,0.826385,0.0026842,0.0006011636,0.003327928,0.001017336,0.0005193781,0.003701804],"genre_scores_gemma":[0.7216207,0.0004776594,0.2507594,0.001402836,0.0007641428,0.01080556,0.001166307,0.0001070345,0.01289639],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2245589,"threshold_uncertainty_score":0.956257,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3121876663","doi":"10.1111/rssa.12386","title":"A Bayesian Time Varying Approach to Risk Neutral Density Estimation","year":2018,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Seventh Framework Programme; Global Risk Institute in Financial Services","keywords":"Smoothing; Bayesian probability; Econometrics; Mathematics; Multivariate statistics; Risk neutral; Volatility (finance); Density estimation; Estimation; Derivative (finance); Smoothing spline; Statistics; Economics; Spline interpolation","authors":[{"name":"Roberto Casarin","is_ca":false},{"name":"Germán Molina","is_ca":false},{"name":"Enrique ter Horst","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01627021884738787,"gpt":0.2303867453432682,"spread":0.2141165264958803,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01151073,0.001020226,0.001954841,0.002275412,0.0007867331,0.003182385,0.004025245,0.002705434,0.008284222],"category_scores_gemma":[0.04739913,0.001445454,0.00204907,0.00227597,0.00216671,0.004504504,0.002643146,0.005174025,0.001325902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002494136,"about_ca_system_score_gemma":0.002150774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01172067,"about_ca_topic_score_gemma":0.009854447,"domain_scores_codex":[0.9951551,0.002909324,0.0001999336,0.0007009827,0.0007992898,0.0002353972],"domain_scores_gemma":[0.9805452,0.01542658,0.001112481,0.001110192,0.001451724,0.0003538947],"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":[0.0000374146,0.00004503062,0.000999219,0.00008769157,0.0001249328,0.0001337078,0.0001715909,0.3285735,0.0003232415,0.6355498,0.002552151,0.03140165],"study_design_scores_gemma":[0.000009350093,0.00001194158,0.0003124659,0.00005281359,0.00002336109,0.00004919723,0.0000205802,0.6956931,0.0001213277,0.3010293,0.002643241,0.00003328108],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00244507,0.0003917017,0.9947191,0.000472724,0.00004204344,0.00002033185,0.000117898,0.00008473139,0.001706355],"genre_scores_gemma":[0.3358302,0.003528424,0.6355405,0.0007729187,0.000836474,0.0004994807,0.001299046,0.0005072377,0.02118581],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01172067,"threshold_uncertainty_score":0.0608753,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1677380367","doi":"10.1111/j.1467-985x.2011.00685.x","title":"Assessing Variance Components in Multilevel Linear Models using Approximate Bayes Factors: A Case-Study of Ethnic Disparities in Birth Weight","year":2011,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Birth, Development, and Health","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; National Institute of Environmental Health Sciences; National Institutes of Health","keywords":"Random effects model; Bayes' theorem; Multilevel model; Statistics; Mathematics; Linear model; Bayes factor; Heteroscedasticity; Generalized linear mixed model; Econometrics; Medicine; Bayesian probability; Meta-analysis","authors":[{"name":"Benjamin R. Saville","is_ca":false},{"name":"Amy H. Herring","is_ca":false},{"name":"Jay S. Kaufman","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1563852242021677,"gpt":0.3563554917791978,"spread":0.1999702675770301,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04443299,0.0006244801,0.001418765,0.0014671,0.00124939,0.001979793,0.001610856,0.002042937,0.001368932],"category_scores_gemma":[0.1335479,0.0005762933,0.002302317,0.001773719,0.001750453,0.001825629,0.002657984,0.00224716,0.00008733694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001065624,"about_ca_system_score_gemma":0.00152353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01777515,"about_ca_topic_score_gemma":0.01856493,"domain_scores_codex":[0.9749779,0.02224781,0.000526389,0.0008909646,0.0009079661,0.0004490157],"domain_scores_gemma":[0.8553399,0.134512,0.003759888,0.004450052,0.001444206,0.000494025],"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":[0.0009244751,0.0006466907,0.6118797,0.0004545445,0.002365497,0.008775502,0.01222172,0.08353305,0.001320763,0.1471391,0.002541615,0.1281974],"study_design_scores_gemma":[0.0002050374,0.0004305811,0.05883474,0.0002451516,0.001057672,0.002887582,0.005447955,0.7487469,0.0006640881,0.179393,0.001971416,0.0001157805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7252893,0.001179438,0.2687732,0.002809419,0.00005120908,0.00015414,0.000125929,0.00005853819,0.001558972],"genre_scores_gemma":[0.9208687,0.0003199736,0.078173,0.00009769631,0.00004035196,0.0001266191,0.00004617726,0.000025138,0.0003023766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04443299,"threshold_uncertainty_score":0.2349869,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4393138778","doi":"10.1093/jrsssa/qnae027","title":"What does rally length tell us about player characteristics in tennis?","year":2024,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series A (Statistics in Society)","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia; Simon Fraser University","funders":"Canadian Statistical Sciences Institute; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Data science","authors":[{"name":"Nirodha Epasinghege Dona","is_ca":true},{"name":"Paramjit Gill","is_ca":true},{"name":"Tim B. Swartz","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01151480224061685,"gpt":0.2292542825988946,"spread":0.2177394803582778,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0101924,0.0004889349,0.001273458,0.00126675,0.0005620632,0.004111303,0.001375714,0.001646243,0.008321923],"category_scores_gemma":[0.05827574,0.0004434866,0.00111889,0.002133046,0.001803576,0.003141069,0.001605951,0.003309777,0.002192773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008792639,"about_ca_system_score_gemma":0.0006383492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01389995,"about_ca_topic_score_gemma":0.01330374,"domain_scores_codex":[0.9969835,0.001567155,0.0001493957,0.000705704,0.0002494552,0.0003447653],"domain_scores_gemma":[0.9376336,0.04318385,0.01145042,0.004183798,0.001278735,0.00226959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008268846,0.0002402966,0.9465623,0.0001052859,0.0005264911,0.0001454439,0.0008681211,0.02337007,0.0003528347,0.006510586,0.004089047,0.01640258],"study_design_scores_gemma":[0.00008955081,0.0004496849,0.8275031,0.0002086772,0.0003389273,0.0002536326,0.003186678,0.1243006,0.0006855195,0.03560072,0.007213791,0.0001689952],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9659837,0.001078925,0.01780914,0.005062285,0.0001369707,0.00003604986,0.005028694,0.0001197764,0.004744561],"genre_scores_gemma":[0.9953491,0.0001844243,0.0007088882,0.0001498195,0.00007598807,0.0000188701,0.002067703,0.00002522971,0.001419993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01389995,"threshold_uncertainty_score":0.05390316,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}