{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":145,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":145,"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"},"query_hash":"e2bb29ba1473","filters":{"venue":"Journal of Statistical Planning and Inference"}},"results":[{"id":"W2031617595","doi":"10.1016/j.jspi.2007.03.029","title":"Proportional reversed hazard rate model and its applications","year":2007,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":237,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Hazard; Monotonic function; Hazard ratio; Statistics; Proportional hazards model; Econometrics; Inference; Fisher information; Applied mathematics; Mathematical analysis; Computer science; Artificial intelligence; Confidence interval","retraction":null,"screen_n_in":null,"score":{"opus":0.1079574168429293,"gpt":0.4177816698030755,"spread":0.3098242529601462,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006248845,0.00008963489,0.0001778631,0.00006141081,0.0001347563,0.00003902278,0.00005870757,0.00005006168,0.00005039466],"category_scores_gemma":[0.002174524,0.00007439791,0.00001667162,0.00008847996,0.0001090937,0.0001106256,0.00002033222,0.0002026015,0.000005055681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002090288,"about_ca_system_score_gemma":0.00007253487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.257514e-7,"about_ca_topic_score_gemma":4.169469e-7,"domain_scores_codex":[0.9990297,0.00002178214,0.0005052247,0.0001101244,0.0001928076,0.0001403447],"domain_scores_gemma":[0.9973961,0.001781747,0.0002491673,0.00005642184,0.0003028355,0.0002137289],"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":[0.00003005059,0.00005487089,0.0002755875,0.0000487595,0.00001163609,0.000007731541,0.00006441876,0.00008941934,0.0004187549,0.9948604,0.00137322,0.00276519],"study_design_scores_gemma":[0.0005885242,0.000105013,0.03446429,0.0001124656,0.00008182844,0.0001090017,0.0001434893,0.1183389,0.0001434151,0.8447639,0.0009614016,0.0001877505],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01782063,0.00006288385,0.9807971,0.0002831175,0.00001465099,0.0001134812,0.0001732964,0.0000150316,0.0007198495],"genre_scores_gemma":[0.8587491,0.0000206937,0.1409908,0.0001027401,0.0000342087,0.000006161421,0.00001592685,0.000005201538,0.00007519569],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8409284,"threshold_uncertainty_score":0.3033859,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2000093045","doi":"10.1016/j.jspi.2008.03.036","title":"Exact inference for a simple step-stress model with competing risks for failure from exponential distribution under Type-II censoring","year":2008,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":138,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Censoring (clinical trials); Accelerated life testing; Estimator; Exponential distribution; Applied mathematics; Statistics; Inference; Exponential function; Monte Carlo method; Parametric statistics; Statistical inference; Weibull distribution; Computer science; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.1648313708267644,"gpt":0.4107405642197369,"spread":0.2459091933929725,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001663361,0.0001530995,0.000316262,0.00003421366,0.0004322095,0.00005641717,0.00009934104,0.00006387624,0.0000348675],"category_scores_gemma":[0.002408545,0.0001221844,0.00003633878,0.00007839673,0.0001385208,0.0001480809,0.00002848175,0.0002063481,8.039643e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004285302,"about_ca_system_score_gemma":0.0001082702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001613156,"about_ca_topic_score_gemma":0.000004006082,"domain_scores_codex":[0.9988409,0.00002999209,0.000500332,0.0001738732,0.0002321191,0.0002227611],"domain_scores_gemma":[0.9952357,0.003614787,0.0003494945,0.00009449115,0.0005367586,0.000168766],"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":[0.0007109409,0.0003409388,0.004244232,0.0002040982,0.0001290212,0.00001401208,0.0006599549,0.01256932,0.0004660116,0.9714419,0.006877023,0.002342545],"study_design_scores_gemma":[0.002140908,0.0006484434,0.01581286,0.0004155757,0.0002095532,0.00004429162,0.0006052889,0.7651986,0.0003466191,0.2137695,0.0004596147,0.0003486554],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1408062,0.00001678122,0.8545906,0.0001073376,0.00002569699,0.0001784192,0.004232747,0.00001955186,0.00002267146],"genre_scores_gemma":[0.7556357,0.000006643407,0.2437677,0.0000208339,0.00005401398,0.00001689973,0.0004801693,0.000009389893,0.000008656672],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7576724,"threshold_uncertainty_score":0.4982534,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1968723219","doi":"10.1016/j.jspi.2005.11.011","title":"Estimating conditional tail expectation with actuarial applications in view","year":2008,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":110,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"Indiana University Bloomington","keywords":"Estimator; Mathematics; Parametric statistics; Conditional expectation; Econometrics; Construct (python library); Asymptotic analysis; Mathematical economics; Applied mathematics; Statistics; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.0892378011964783,"gpt":0.4007101723045575,"spread":0.3114723711080792,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005090437,0.00007327901,0.0002097922,0.0001849487,0.0001401102,0.00007462577,0.0001070252,0.00003495093,0.00006610846],"category_scores_gemma":[0.001476181,0.00004736485,0.00001437803,0.0002660634,0.0001288788,0.0003784484,0.00001186071,0.0001686724,0.000004875829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001466518,"about_ca_system_score_gemma":0.0001406956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008329406,"about_ca_topic_score_gemma":0.000001533864,"domain_scores_codex":[0.9985858,0.00006686452,0.0005741254,0.0001224131,0.0005519862,0.00009881822],"domain_scores_gemma":[0.9972866,0.00188208,0.0003780424,0.00006307029,0.0002983824,0.00009178329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002685356,0.0001563766,0.7886259,0.00001118708,0.00002341414,0.0002081592,0.004956636,0.137962,0.00006012395,0.02583238,0.002466233,0.03942908],"study_design_scores_gemma":[0.001004771,0.0004314474,0.8533356,0.0001208683,0.00001934758,0.0003566524,0.0009882289,0.09017067,0.00002090289,0.05226097,0.001110339,0.0001802765],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1997323,0.00006066631,0.7996389,0.00005839485,0.0000411404,0.00004692522,0.00001362968,0.000003406787,0.0004046411],"genre_scores_gemma":[0.8921151,0.00003713758,0.1077067,0.0000291706,0.00007429269,0.0000033378,0.00001448369,0.000002816822,0.00001705406],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6923827,"threshold_uncertainty_score":0.1931482,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2045722221","doi":"10.1016/j.jspi.2007.05.028","title":"Connections of the Poisson weight function to overdispersion and underdispersion","year":2007,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Mathematical Inequalities and Applications","field":"Mathematics","cited_by":94,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Overdispersion; Mathematics; Poisson distribution; Pointwise; Weight function; Function (biology); Quasi-likelihood; Applied mathematics; Poisson regression; Statistics; Mathematical analysis; Count data","retraction":null,"screen_n_in":null,"score":{"opus":0.06063624366315861,"gpt":0.3724164393088247,"spread":0.3117801956456661,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004505276,0.00006310812,0.0001606372,0.00004766222,0.0001138236,0.00001801234,0.00005309248,0.00003938569,0.00004572972],"category_scores_gemma":[0.0008505015,0.00003826089,0.00002512738,0.00008890038,0.00007273206,0.00005537606,0.00004261083,0.0001391707,7.400038e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001486573,"about_ca_system_score_gemma":0.00001528188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000899524,"about_ca_topic_score_gemma":0.000002651073,"domain_scores_codex":[0.9992839,0.00002444582,0.0003533613,0.00006556415,0.0001766208,0.00009607959],"domain_scores_gemma":[0.9978648,0.001679873,0.0001708078,0.00007451793,0.0001033266,0.0001066337],"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":[0.00006116127,0.00006032912,0.001801839,0.00009777775,0.00001806951,0.00000139473,0.0007741659,0.000007591903,0.001731529,0.9915255,0.002028596,0.001892074],"study_design_scores_gemma":[0.0005618789,0.00065207,0.07692622,0.0008073836,0.0001703066,0.00009304798,0.004369411,0.001439293,0.001251854,0.910827,0.002723097,0.0001784577],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3548331,0.00004238003,0.6432316,0.00051496,0.00006184174,0.00006057808,0.00001323472,0.000003886666,0.00123845],"genre_scores_gemma":[0.9841106,0.000009306343,0.015686,0.00007928948,0.00004156622,5.237001e-7,4.898425e-7,0.000003967862,0.00006827317],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6292775,"threshold_uncertainty_score":0.1560234,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2076470657","doi":"10.1016/j.jspi.2011.03.026","title":"On the robustness of maximum composite likelihood estimate","year":2011,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":91,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Robustness (evolution); Multivariate statistics; Likelihood function; Maximum likelihood; Quasi-maximum likelihood; Statistics; Marginal likelihood; Composite number; Consistency (knowledge bases); Applied mathematics; Econometrics; Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.166988026560952,"gpt":0.4196647308178981,"spread":0.252676704256946,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005846124,0.0001168345,0.0003380497,0.00004726077,0.00007001257,0.000016201,0.0001375432,0.00004367778,0.00007836297],"category_scores_gemma":[0.002833518,0.00006697552,0.00003071883,0.00005312245,0.0001883129,0.00007311704,0.00003568194,0.0003144266,9.22278e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008307358,"about_ca_system_score_gemma":0.00003096728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003283379,"about_ca_topic_score_gemma":2.413298e-7,"domain_scores_codex":[0.9989089,0.0001094791,0.0004871949,0.0000944088,0.0002278471,0.0001722026],"domain_scores_gemma":[0.9938388,0.005419805,0.0003362023,0.0001088814,0.0001741446,0.0001221202],"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":[0.0002756411,0.0001674977,0.0004129839,0.0001054763,0.00004667465,0.00006280115,0.0006832269,0.0003146,0.0001991767,0.9820791,0.0005058166,0.01514704],"study_design_scores_gemma":[0.0002725521,0.0005667906,0.002881458,0.00038525,0.00005949872,0.000046034,0.0001045142,0.01185642,0.000317691,0.9834082,0.00001067394,0.00009098134],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06379966,0.00004531099,0.934594,0.00004626583,0.00008280441,0.00004953892,0.00004445281,0.000005820286,0.0013321],"genre_scores_gemma":[0.514395,0.000007238014,0.4855433,0.00002716548,0.00001514503,7.641369e-7,3.564876e-7,0.000005921332,0.000005065893],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4505953,"threshold_uncertainty_score":0.339219,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2053287005","doi":"10.1016/j.jspi.2006.04.017","title":"Exact inference for a simple step-stress model with Type-II hybrid censored data from the exponential distribution","year":2007,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":82,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Exponential distribution; Accelerated life testing; Estimator; Applied mathematics; Statistics; Moment (physics); Monte Carlo method; Parametric statistics; Exponential function; Order statistic; Weibull distribution; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.1297260088054976,"gpt":0.4146277630886851,"spread":0.2849017542831875,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004946691,0.0001348754,0.0002378632,0.00002150599,0.000290933,0.00009103749,0.0002783721,0.0000447383,0.00006292664],"category_scores_gemma":[0.004804065,0.00008594412,0.00001905395,0.00008904914,0.0001743353,0.000183029,0.0000851219,0.0002393191,0.00000186946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002879697,"about_ca_system_score_gemma":0.0001146111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000188277,"about_ca_topic_score_gemma":0.000008717233,"domain_scores_codex":[0.9987385,0.00003452551,0.0005211054,0.0001850514,0.0003024644,0.0002183016],"domain_scores_gemma":[0.9935936,0.005263443,0.0003287849,0.0002522716,0.0003980631,0.0001637897],"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":[0.00120212,0.000451581,0.00342209,0.00009661149,0.0001514791,0.00003463163,0.0004285215,0.0009172215,0.0003706751,0.9154105,0.06397215,0.01354246],"study_design_scores_gemma":[0.001575743,0.0005119704,0.03410583,0.0003167842,0.0003108051,0.00004037061,0.0004517674,0.7275513,0.0002937324,0.2324449,0.002074978,0.0003218009],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04380418,0.0000325263,0.9427072,0.0001815885,0.00003595018,0.0001479188,0.01301891,0.00001561483,0.00005612007],"genre_scores_gemma":[0.8843889,0.000008947374,0.1135392,0.00005355118,0.00007515009,0.00000353193,0.001911863,0.000007910577,0.00001094014],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8405848,"threshold_uncertainty_score":0.5751262,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2017956206","doi":"10.1016/j.jspi.2008.07.008","title":"Bayes estimation based on -record data from a general class of distributions under balanced type loss functions","year":2008,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":71,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Mathematics; Weibull distribution; Estimator; Bayes' theorem; Bayes estimator; Statistics; Type (biology); Exponential function; Mean squared error; Parametric statistics; Applied mathematics; Exponential family; Pareto distribution; Prior probability; Class (philosophy); Pareto principle; Exponential type; Estimation; Bayesian probability; Computer science; Mathematical analysis; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.1603878237965399,"gpt":0.4047650518887529,"spread":0.244377228092213,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001695189,0.0001180577,0.0002793438,0.00006588677,0.000166321,0.00002623661,0.0001639036,0.00006397389,0.0002982742],"category_scores_gemma":[0.003543317,0.00009861581,0.00002546881,0.0001760012,0.0002261335,0.0001393583,0.00003410387,0.0002321261,0.00001333282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003633988,"about_ca_system_score_gemma":0.0001619995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002065241,"about_ca_topic_score_gemma":0.000001897754,"domain_scores_codex":[0.9987653,0.00006447977,0.000580765,0.0001643702,0.0002939621,0.0001311002],"domain_scores_gemma":[0.9959727,0.00297378,0.0003412317,0.0002446041,0.0003214069,0.0001462891],"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":[0.0003847983,0.0007969726,0.01320868,0.00007983834,0.0001106239,0.00003910984,0.0001086811,0.00703492,0.0003805451,0.9204493,0.05282718,0.004579384],"study_design_scores_gemma":[0.0008451017,0.0003145088,0.1711483,0.0002044921,0.0001244063,0.00002850371,0.00005354009,0.6909555,0.0000558951,0.1355912,0.0005072089,0.0001713667],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05893748,0.00001723099,0.935625,0.0003311488,0.00008724903,0.00006247746,0.004662947,0.00001714519,0.00025939],"genre_scores_gemma":[0.8580608,0.00001010981,0.140858,0.00006701185,0.00004249054,0.000002389923,0.0009300431,0.000006140887,0.00002295316],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7991234,"threshold_uncertainty_score":0.4241937,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4232947516","doi":"10.1016/j.jspi.2007.03.011","title":"Exact inference for a simple step-stress model with Type-I hybrid censored data from the exponential distribution","year":2007,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":66,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Exponential distribution; Estimator; Accelerated life testing; Applied mathematics; Statistics; Monte Carlo method; Moment (physics); Parametric statistics; Parametric model; Delta method; Exponential function; Inference; Weibull distribution; Mathematical analysis; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.1344027248027278,"gpt":0.4180899922856365,"spread":0.2836872674829087,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004934187,0.0001298173,0.0002309688,0.00002061082,0.0001977913,0.000103386,0.0002709083,0.00004278984,0.00004911014],"category_scores_gemma":[0.004888681,0.00008268584,0.00001828696,0.00008574363,0.0001714107,0.0001770909,0.00006142762,0.0002327291,0.000002342904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002791486,"about_ca_system_score_gemma":0.0001117416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001932821,"about_ca_topic_score_gemma":0.000008682238,"domain_scores_codex":[0.9987721,0.00003559067,0.0005073213,0.0001789027,0.0002949681,0.0002110512],"domain_scores_gemma":[0.9927053,0.006181003,0.0003193012,0.0002465509,0.0003878945,0.0001599859],"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":[0.001097539,0.0003446694,0.004236903,0.00009545057,0.0001358749,0.00003538994,0.0002706834,0.0008484194,0.0003241114,0.9220097,0.05888635,0.0117149],"study_design_scores_gemma":[0.00148806,0.0003684376,0.03916567,0.0003007175,0.0002979527,0.00003936216,0.0004631982,0.7252194,0.0002829882,0.2303789,0.001690098,0.0003052553],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03316837,0.00003620214,0.9536689,0.0001509177,0.00003505339,0.0001458924,0.01273063,0.00001511534,0.00004894114],"genre_scores_gemma":[0.8786587,0.00001059491,0.119362,0.00005194803,0.00007244903,0.000003338257,0.001824948,0.000007736759,0.000008236764],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8454903,"threshold_uncertainty_score":0.5852561,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2042654193","doi":"10.1016/j.jspi.2010.07.005","title":"A Jonckheere–Terpstra-type test for perfect ranking in balanced ranked set sampling","year":2010,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":62,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Ranking (information retrieval); Nonparametric statistics; Statistics; RSS; Statistic; Test statistic; Sampling (signal processing); Type I and type II errors; Type (biology); Test (biology); Set (abstract data type); Statistical hypothesis testing; Algorithm; Artificial intelligence; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.1232962016839542,"gpt":0.4428703394002491,"spread":0.3195741377162948,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0005494643,0.0001145066,0.0002930029,0.00007990912,0.0001019109,0.00007505699,0.0001007705,0.00007570988,0.00009847159],"category_scores_gemma":[0.01323934,0.00009627258,0.00002911168,0.0001258601,0.0000983734,0.00009899266,0.00001464043,0.0004229336,0.000002598681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001872751,"about_ca_system_score_gemma":0.00008071251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003612536,"about_ca_topic_score_gemma":0.000003773204,"domain_scores_codex":[0.9989272,0.00002626544,0.0005560663,0.0001267846,0.0001700052,0.0001936544],"domain_scores_gemma":[0.9916888,0.007630634,0.0002158308,0.00008228825,0.0002504046,0.0001319713],"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":[0.0002079024,0.0002054349,0.01911461,0.0002109458,0.00003300629,0.00001941419,0.0006143709,0.00008105573,0.0110682,0.9578018,0.001983566,0.008659678],"study_design_scores_gemma":[0.003416912,0.0006495969,0.2089647,0.0006291782,0.0001242819,0.000175695,0.0003314147,0.08168995,0.0004056362,0.7019167,0.001246695,0.0004492405],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1564262,0.00001624773,0.8426952,0.0001647235,0.0001002636,0.0001250209,0.00026734,0.00001358696,0.0001914188],"genre_scores_gemma":[0.8325961,0.000004381349,0.1672443,0.00005300512,0.0000551702,0.000006826194,0.00002560069,0.000007403059,0.000007229548],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6761699,"threshold_uncertainty_score":0.9950725,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1999057766","doi":"10.1016/s0378-3758(99)00092-0","title":"Some alternative strategies to Moors’ model in randomized response sampling","year":2000,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":52,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Randomized response; Moors; Mathematics; Efficiency; Statistics; Econometrics; Sampling (signal processing); Mathematical economics; Geography; Computer science; Archaeology","retraction":null,"screen_n_in":null,"score":{"opus":0.1514197559372908,"gpt":0.4420925287823689,"spread":0.2906727728450781,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002889216,0.0001164778,0.0005183451,0.0001947178,0.00004801325,0.00009693664,0.0001034788,0.00005115604,0.00003964537],"category_scores_gemma":[0.006274376,0.00008954072,0.0000350269,0.00007926658,0.00006931012,0.0002698838,0.00001544534,0.0002704663,0.000002669914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002935845,"about_ca_system_score_gemma":0.00009796278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003105032,"about_ca_topic_score_gemma":0.000001291442,"domain_scores_codex":[0.9985901,0.0002826206,0.0006408191,0.0001094783,0.0002163628,0.0001606622],"domain_scores_gemma":[0.9914947,0.008049512,0.0001636041,0.00007111318,0.0001071277,0.0001139046],"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":[0.1449924,0.0003233948,0.0008316622,0.0001854785,0.000151691,0.0002073168,0.02291864,0.2953005,0.0008262912,0.5010056,0.001402383,0.03185464],"study_design_scores_gemma":[0.005818464,0.0001671732,0.001029438,0.0004933984,0.00001816951,0.00002241377,0.000234048,0.1345531,0.0000828563,0.8574381,0.0000146951,0.0001280476],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.424747,0.00005775482,0.5748519,0.00009180007,0.00001926985,0.0000640171,0.00001398132,0.00001544049,0.0001388648],"genre_scores_gemma":[0.7276586,0.00004626848,0.2721678,0.00005769545,0.00002849161,0.00000419738,9.449612e-7,0.000006595727,0.00002942475],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3564326,"threshold_uncertainty_score":0.7511467,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1990707483","doi":"10.1016/j.jspi.2012.03.016","title":"On the boundary properties of Bernstein polynomial estimators of density and distribution functions","year":2012,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":47,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Estimator; Mathematics; Bernstein polynomial; Smoothness; Boundary (topology); Polynomial; Kernel density estimation; Distribution (mathematics); Probability density function; Applied mathematics; Kernel (algebra); Variance (accounting); Function (biology); Statistics; Mathematical analysis; Combinatorics","retraction":null,"screen_n_in":null,"score":{"opus":0.0310017223909433,"gpt":0.2730664508634813,"spread":0.242064728472538,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001447086,0.00004869435,0.0001179446,0.00001457696,0.00007666998,0.0000144362,0.00002438746,0.00001686116,0.00002515288],"category_scores_gemma":[0.00006448522,0.00002841629,0.00001691762,0.00002508279,0.0001550744,0.00008399209,0.00001400621,0.000160255,2.925573e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000403378,"about_ca_system_score_gemma":0.000025926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001897268,"about_ca_topic_score_gemma":9.830103e-8,"domain_scores_codex":[0.9995833,0.00002862255,0.0001885968,0.00003520329,0.00009171949,0.00007256955],"domain_scores_gemma":[0.9994857,0.0002185752,0.0001470071,0.00003221939,0.0000576539,0.00005886356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001027861,0.0005034227,0.5961248,0.0001371085,0.0002364115,0.000002395544,0.002012555,0.001323989,0.0071097,0.3425428,0.01174414,0.03723487],"study_design_scores_gemma":[0.002679627,0.002699531,0.8790839,0.002698802,0.0005724842,0.0001492779,0.005007791,0.04146777,0.02881142,0.03364239,0.00241956,0.0007674606],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9038584,0.0001151427,0.09570416,0.00006686914,0.00008889094,0.00002163229,0.00003436534,0.000001007383,0.0001095233],"genre_scores_gemma":[0.999711,0.000004378222,0.0001755088,0.000008086882,0.00008083753,3.890484e-7,0.000003518088,0.000001667375,0.00001457167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3089004,"threshold_uncertainty_score":0.1158782,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2076905182","doi":"10.1016/j.jspi.2004.01.018","title":"A note on the number of observations near an order statistic","year":2004,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":46,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Order statistic; Independent and identically distributed random variables; Combinatorics; Random variable; Sequence (biology); Independence (probability theory); Statistics; Statistic; Order (exchange); Interval (graph theory); Limit (mathematics); Distribution (mathematics); Asymptotic distribution; Discrete mathematics; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.2257332368225606,"gpt":0.4524361247702367,"spread":0.2267028879476761,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001667062,0.0000838557,0.0002432719,0.00004520438,0.0001831163,0.0001580351,0.0002983515,0.00004544733,0.000132039],"category_scores_gemma":[0.01215399,0.00004293966,0.00002655122,0.0002397174,0.0003578718,0.0002912367,0.00003367694,0.000304523,0.00001531742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001711535,"about_ca_system_score_gemma":0.000275229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005195765,"about_ca_topic_score_gemma":0.000007309202,"domain_scores_codex":[0.998171,0.0001554423,0.000667971,0.0001359869,0.0007383139,0.0001312583],"domain_scores_gemma":[0.993191,0.005552635,0.0003446017,0.0001872585,0.000596032,0.0001284446],"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":[0.000209791,0.000257998,0.03292986,0.00001327383,0.00002216662,0.00004379273,0.004214549,0.03831424,0.0001272638,0.9082159,0.0007759444,0.01487527],"study_design_scores_gemma":[0.0002925557,0.0003845967,0.1541556,0.0001015927,0.00001515529,0.00003350491,0.0002984519,0.01595677,0.00002081723,0.8284127,0.0002581929,0.00007002601],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4298917,0.00001701709,0.5688747,0.0007790332,0.00006187785,0.00003248874,0.00006738925,0.000002471265,0.0002733115],"genre_scores_gemma":[0.9085115,0.000008696812,0.09119395,0.0002403678,0.00002315307,6.491488e-7,0.000001364463,0.000002979741,0.00001735229],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4786197,"threshold_uncertainty_score":0.9961671,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1985405042","doi":"10.1016/s0378-3758(00)00076-8","title":"Two matrix-based proofs that the linear estimator Gy is the best linear unbiased estimator","year":2000,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Mathematics; Transpose; Best linear unbiased prediction; Matrix (chemical analysis); Bias of an estimator; Combinatorics; Estimator; Minimum-variance unbiased estimator; Applied mathematics; Discrete mathematics; Statistics; Selection (genetic algorithm); Eigenvalues and eigenvectors","retraction":null,"screen_n_in":null,"score":{"opus":0.03362893076150036,"gpt":0.3368422009544101,"spread":0.3032132701929098,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009611985,0.0001967708,0.0002852821,0.000058763,0.00045442,0.0002938716,0.0008022808,0.00005547501,0.0001820342],"category_scores_gemma":[0.0004201072,0.0001019779,0.00006292415,0.0002020337,0.0002867024,0.0003154933,0.00006465681,0.0005652228,0.00005144432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001557429,"about_ca_system_score_gemma":0.0002086147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001625858,"about_ca_topic_score_gemma":3.299922e-7,"domain_scores_codex":[0.9983667,0.0001985201,0.0004529486,0.0002133915,0.0004659671,0.0003024815],"domain_scores_gemma":[0.9968045,0.002294746,0.0002484675,0.0003147445,0.0001366209,0.000200938],"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":[0.001118386,0.0008527748,0.01491193,0.0003992422,0.0003539468,0.002030964,0.00586773,0.06837581,0.0002695514,0.4941103,0.01458411,0.3971253],"study_design_scores_gemma":[0.0008273878,0.0005033441,0.001369888,0.0002904079,0.00005630562,0.0002902532,0.0001306365,0.9717427,0.0004214338,0.01942445,0.004710467,0.0002327336],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02103635,0.0004354061,0.9745362,0.003108069,0.0001865378,0.0001319535,0.0000455353,0.00003260209,0.000487397],"genre_scores_gemma":[0.7905046,0.00002879057,0.2079986,0.001021408,0.0002218752,0.000004399379,0.00000234857,0.00001185493,0.0002060217],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9033669,"threshold_uncertainty_score":0.4158536,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1982364633","doi":"10.1016/j.jspi.2009.03.024","title":"Analytic bounds on causal risk differences in directed acyclic graphs involving three observed binary variables","year":2009,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":41,"is_retracted":false,"has_abstract":false,"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","keywords":"Mathematics; Directed acyclic graph; Combinatorics; Covariate; Monotonic function; Binary number; Upper and lower bounds; Measure (data warehouse); Discrete mathematics; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.1552871777379599,"gpt":0.3901827679038079,"spread":0.234895590165848,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007984693,0.0002891457,0.0007280087,0.0003929283,0.0001391153,0.0001276881,0.0002587702,0.0001492566,0.00003555061],"category_scores_gemma":[0.006061313,0.0002208404,0.00005327144,0.0003700186,0.0002152239,0.000372745,0.00004400992,0.0009538045,0.000001130762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007882134,"about_ca_system_score_gemma":0.00009420305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004838255,"about_ca_topic_score_gemma":0.00002602616,"domain_scores_codex":[0.9978309,0.0001946527,0.0009017188,0.000259346,0.0004245342,0.0003888567],"domain_scores_gemma":[0.994278,0.00453595,0.0006152708,0.0001939155,0.0001746067,0.000202332],"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":[0.0005323136,0.0006592475,0.5120233,0.0001276671,0.0001202386,0.0006771588,0.001083434,0.0001732351,0.002165963,0.469593,0.001012344,0.01183202],"study_design_scores_gemma":[0.0003340869,0.001122753,0.381965,0.000777685,0.00005123985,0.00002126363,0.0000894938,0.005496654,0.00006807179,0.6098804,0.000004981986,0.000188333],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8601053,0.0003358087,0.1387935,0.00008333677,0.00007379876,0.0001100731,0.00003265557,0.00009682713,0.0003687756],"genre_scores_gemma":[0.9367703,0.0002706864,0.06281599,0.00007120029,0.00004054268,0.000002931641,0.000004258922,0.00001309038,0.00001098695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1402874,"threshold_uncertainty_score":0.9005612,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1984072874","doi":"10.1016/j.jspi.2012.10.009","title":"An alternative to unit root tests: Bridge estimators differentiate between nonstationary versus stationary models and select optimal lag","year":2012,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":37,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Unit root; Estimator; Mathematics; Lag; Selection (genetic algorithm); Model selection; Limit (mathematics); Statistics; Stationary process; Plot (graphics); Applied mathematics; Mathematical optimization; Computer science; Artificial intelligence; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.2072641134721543,"gpt":0.4585828778034047,"spread":0.2513187643312504,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007125511,0.0002459591,0.0004900874,0.0001833353,0.0001635731,0.0001134868,0.0001613473,0.00007999954,0.00005247593],"category_scores_gemma":[0.003326393,0.0002027689,0.00002550115,0.0001484922,0.0001689423,0.0006329424,0.00007239573,0.0004186433,0.000003322149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003807165,"about_ca_system_score_gemma":0.00009646743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002543921,"about_ca_topic_score_gemma":0.00000141607,"domain_scores_codex":[0.9980391,0.0002508859,0.0006572838,0.0002140845,0.0004396109,0.0003990966],"domain_scores_gemma":[0.990145,0.008391803,0.0003039108,0.0001180606,0.0003327178,0.000708502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.001022023,0.000469479,0.2530378,0.0002217162,0.0003199046,0.0001005168,0.005993698,0.001668287,0.0002231776,0.6780462,0.00103699,0.05786023],"study_design_scores_gemma":[0.001136126,0.001966818,0.6915256,0.0003123008,0.0002085898,0.00006777429,0.0003701763,0.03907123,0.00007290969,0.2648183,0.00003769541,0.0004124546],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4461869,0.00007125489,0.5531539,0.00003715393,0.00008943693,0.00006949351,0.000255333,0.000012521,0.0001239238],"genre_scores_gemma":[0.6318137,0.00001025031,0.3679958,0.00002764005,0.0001147424,0.000003319076,0.00001610322,0.00001429179,0.000004202552],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4384879,"threshold_uncertainty_score":0.8268676,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2057200769","doi":"10.1016/j.jspi.2009.03.003","title":"General frailty model and stochastic orderings","year":2009,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":34,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of New Brunswick","funders":"","keywords":"Mathematics; Multiplicative function; Stochastic ordering; Stochastic modelling; Applied mathematics; Statistics; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.04300626722078061,"gpt":0.363052563037092,"spread":0.3200462958163114,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005263299,0.00009136315,0.0001968811,0.00008873745,0.000242868,0.0001279994,0.0001039124,0.00004979287,0.00001564718],"category_scores_gemma":[0.0004175926,0.00007852466,0.00002120555,0.00008682522,0.0002482679,0.0002198406,0.00002068934,0.0002242229,8.801882e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001747372,"about_ca_system_score_gemma":0.00006749677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008743429,"about_ca_topic_score_gemma":0.00001383681,"domain_scores_codex":[0.998996,0.00005226943,0.0002756587,0.0001158838,0.0003395523,0.0002206864],"domain_scores_gemma":[0.999327,0.0001810181,0.0001430849,0.00004959668,0.0001141417,0.0001851638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001691267,0.0001676698,0.04195493,0.00005150157,0.00008222586,0.0001667523,0.01267106,0.02104387,0.000165422,0.8227515,0.004102898,0.09667307],"study_design_scores_gemma":[0.0008451317,0.0006358615,0.6359456,0.0002316339,0.0001041392,0.00002467978,0.001356271,0.0896649,0.000002949469,0.2691661,0.00161411,0.000408652],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5533513,0.0003536041,0.4417576,0.0004699063,0.00009819937,0.00006282981,0.00001363625,0.00001467253,0.003878162],"genre_scores_gemma":[0.9837651,0.0001416563,0.01565023,0.0002695283,0.00009901757,5.080072e-7,8.256295e-7,0.000003169295,0.00007000079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5939906,"threshold_uncertainty_score":0.3202143,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2006720822","doi":"10.1016/j.jspi.2004.06.012","title":"Mean residual life estimation","year":2004,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":34,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"","keywords":"Mathematics; Residual; Estimator; Statistics; Survival function; Reliability (semiconductor); Estimation; Applied mathematics; Econometrics; Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.09456679759157226,"gpt":0.4097521186088815,"spread":0.3151853210173092,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000276925,0.0000888645,0.0001960085,0.00005965774,0.0001064234,0.00005960127,0.00007572075,0.00004630894,0.00009130696],"category_scores_gemma":[0.0056581,0.00007247148,0.00001866083,0.00008950588,0.0001193257,0.0001360201,0.00001681063,0.0002032063,0.00001695296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003213259,"about_ca_system_score_gemma":0.0001232356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004268422,"about_ca_topic_score_gemma":6.219054e-7,"domain_scores_codex":[0.9990157,0.00003064631,0.0004821903,0.00008916612,0.000257901,0.0001243618],"domain_scores_gemma":[0.9980696,0.001212585,0.0002346171,0.00007129767,0.000191008,0.0002208952],"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":[0.00002732506,0.00006229975,0.0001235341,0.00002970035,0.00001291388,0.00001286938,0.0002461994,0.0005710631,0.00003525856,0.994306,0.001953878,0.002618927],"study_design_scores_gemma":[0.0007396833,0.0002482757,0.02055451,0.0001768002,0.00005915598,0.00007680361,0.0002116695,0.006183882,0.00007482577,0.9713469,0.0002001688,0.0001273968],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02872828,0.00004521876,0.969716,0.0006862194,0.00004082381,0.00004825256,0.0001124335,0.0000201033,0.0006026847],"genre_scores_gemma":[0.7809024,0.000006061592,0.218924,0.00009843343,0.00003901633,0.000001740157,0.00001473542,0.000004643294,0.000008996044],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7521741,"threshold_uncertainty_score":0.6773683,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2032900910","doi":"10.1016/j.jspi.2011.12.027","title":"LASSO and shrinkage estimation in Weibull censored regression models","year":2012,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":34,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Winnipeg; University of Windsor","funders":"","keywords":"Estimator; Lasso (programming language); Mathematics; Statistics; Shrinkage; Context (archaeology); Regression; Weibull distribution; Regression analysis; Shrinkage estimator; Censoring (clinical trials); Econometrics; Computer science; Efficient estimator; Minimum-variance unbiased estimator","retraction":null,"screen_n_in":null,"score":{"opus":0.08302609011148357,"gpt":0.4028758459350193,"spread":0.3198497558235358,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003855553,0.00009205249,0.0002082713,0.00007580002,0.00006411887,0.00003834407,0.00004482516,0.00005698808,0.00004052514],"category_scores_gemma":[0.001999329,0.00007065164,0.00001161436,0.00008012415,0.00008627775,0.0002879056,0.00002337712,0.0002088139,0.000002707513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002557198,"about_ca_system_score_gemma":0.00002117812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004756897,"about_ca_topic_score_gemma":3.989465e-7,"domain_scores_codex":[0.9990994,0.00005514853,0.0004214243,0.00007780905,0.0001819391,0.0001642605],"domain_scores_gemma":[0.9979882,0.001488834,0.0001944853,0.00005768324,0.00008506368,0.0001857451],"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":[0.0000247951,0.00009606603,0.00408111,0.00004756055,0.000005476838,0.000005820084,0.0003213536,0.0001422656,0.00005502568,0.9893534,0.0007987644,0.00506837],"study_design_scores_gemma":[0.0005723721,0.0000839252,0.1256037,0.0003461836,0.00003405499,0.00007548825,0.0002464643,0.2000035,0.00004526012,0.6727614,0.00009224056,0.0001352931],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08825333,0.0001369945,0.9106321,0.0001618687,0.00003212159,0.00005481514,0.00006585123,0.00000991729,0.0006530234],"genre_scores_gemma":[0.8431897,0.00002666188,0.1567063,0.00003080015,0.00001821038,0.000002525197,0.00001048256,0.000004437406,0.00001089763],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7549363,"threshold_uncertainty_score":0.288109,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2068618230","doi":"10.1016/s0378-3758(99)00185-8","title":"Crossover designs for two-treatment clinical trials","year":2000,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":33,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Crossover; Crossover study; Mathematics; Repeated measures design; Clinical trial; Statistics; Sample size determination; Design of experiments; Optimal design; Sequential analysis; Treatment and control groups; Clinical study design; Computer science; Medicine; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.7098386298084299,"gpt":0.672377921310636,"spread":0.03746070849779393,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01626038,0.0001522756,0.0009337456,0.00009720597,0.0001334544,0.0003706447,0.0002532061,0.00008214239,0.001263815],"category_scores_gemma":[0.03169401,0.00008874269,0.0001856388,0.0001172166,0.0002451774,0.0002889296,0.00002044468,0.0001888658,0.00003649892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003430561,"about_ca_system_score_gemma":0.0001593636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000728087,"about_ca_topic_score_gemma":2.931773e-7,"domain_scores_codex":[0.9953322,0.001412546,0.002147434,0.0002650507,0.0006109321,0.0002318346],"domain_scores_gemma":[0.9520695,0.04653335,0.0006316298,0.0001565398,0.0002747634,0.0003342648],"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":[0.003218303,0.000278601,0.009905938,0.000004371524,0.0001024114,0.00009292165,0.0005152105,0.0008180674,0.001333603,0.008902488,0.00903574,0.9657924],"study_design_scores_gemma":[0.02799615,0.03354097,0.1129515,0.0005198724,0.0006630694,0.0006768259,0.00182569,0.08983385,0.00597553,0.600633,0.1239445,0.001439092],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08902163,0.0005379848,0.9076267,0.0001387687,0.0003579361,0.0001970104,0.0001070912,0.000007419201,0.002005399],"genre_scores_gemma":[0.6173777,0.00005684201,0.3814595,0.0001864719,0.000255707,0.000004551997,0.000001598672,0.000007717722,0.0006499065],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9643533,"threshold_uncertainty_score":0.9996492,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2067423980","doi":"10.1016/j.jspi.2010.09.024","title":"Exact likelihood inference for Laplace distribution based on Type-II censored samples","year":2010,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":32,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Quantile; Laplace distribution; Statistics; Inference; Applied mathematics; Estimator; Exponential function; Order statistic; Scale parameter; Laplace transform; Exponential distribution; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.06510658717298524,"gpt":0.39498469885145,"spread":0.3298781116784648,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0003238248,0.0001417543,0.0002620718,0.0000526298,0.0002548085,0.00007402769,0.000117774,0.00009508643,0.0001949182],"category_scores_gemma":[0.01506458,0.0001136029,0.00003714424,0.0001157061,0.0001434899,0.00008990158,0.0000193676,0.0003807812,0.000005481844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002546675,"about_ca_system_score_gemma":0.0001366707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003205787,"about_ca_topic_score_gemma":0.000001511554,"domain_scores_codex":[0.9988676,0.00003790233,0.000477726,0.000150938,0.0002540316,0.000211828],"domain_scores_gemma":[0.9936157,0.005256661,0.0002832112,0.000129288,0.0004911949,0.0002239135],"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":[0.0001815663,0.0002223084,0.0009822692,0.00006724164,0.00001392095,0.000003891371,0.00006056749,0.00006351065,0.0006462304,0.9794843,0.01168856,0.006585654],"study_design_scores_gemma":[0.002294497,0.002029218,0.094574,0.0004058823,0.0001865432,0.00003817403,0.0001324347,0.1792563,0.0008598836,0.706868,0.0128355,0.0005196094],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02335116,0.000007677188,0.9737765,0.0005399481,0.000150751,0.0001336446,0.001718601,0.00002509278,0.0002966212],"genre_scores_gemma":[0.8811665,0.000004437919,0.1184029,0.0001112991,0.00006541373,0.000008566014,0.0002144136,0.000008138904,0.0000182918],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8578153,"threshold_uncertainty_score":0.993232,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2001450464","doi":"10.1016/j.jspi.2008.05.016","title":"Planning life tests with progressively Type-I interval censored data from the lognormal distribution","year":2008,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":32,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Censoring (clinical trials); Mathematics; Log-normal distribution; Statistics; Interval (graph theory); Maximum likelihood; Interval estimation; Confidence interval; Econometrics; Combinatorics","retraction":null,"screen_n_in":null,"score":{"opus":0.2002180525713284,"gpt":0.4152842945483246,"spread":0.2150662419769962,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002324874,0.0001254998,0.0002390627,0.00001829694,0.0002555696,0.0000698688,0.0002758411,0.00004949975,0.0000782622],"category_scores_gemma":[0.006551094,0.00007473805,0.00001379259,0.0001232404,0.0003352867,0.0002048014,0.00008118797,0.0003465635,0.000006591465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001935538,"about_ca_system_score_gemma":0.0001558279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001038487,"about_ca_topic_score_gemma":9.212745e-7,"domain_scores_codex":[0.9988307,0.00007361642,0.0004525959,0.0001569598,0.0003168869,0.0001692],"domain_scores_gemma":[0.9956563,0.003308519,0.0003449618,0.0001995275,0.0003033634,0.0001872917],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.001217233,0.0006073752,0.1906426,0.0001021564,0.0003428062,0.0005712305,0.001932333,0.0003836111,0.000101291,0.5399556,0.25894,0.005203765],"study_design_scores_gemma":[0.001148186,0.0005231157,0.9210833,0.0006255034,0.0001955316,0.0004436941,0.0005927288,0.03996172,0.00002477903,0.03260836,0.002510688,0.0002823997],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1218023,0.0001376888,0.8754886,0.0004333929,0.00003565402,0.00008021566,0.001890826,0.00001973672,0.0001116252],"genre_scores_gemma":[0.9571736,0.00001329927,0.0420242,0.0001046081,0.00009362871,0.000002499368,0.0005700564,0.000007136657,0.00001093571],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8353714,"threshold_uncertainty_score":0.7842745,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2090131474","doi":"10.1016/j.jspi.2009.09.025","title":"Empirical likelihood based variable selection","year":2009,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":30,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo; University of British Columbia; Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Memorial University of Newfoundland","keywords":"Empirical likelihood; Mathematics; Parametric statistics; Likelihood function; Model selection; Parametric model; Selection (genetic algorithm); Set (abstract data type); Information Criteria; Variable (mathematics); Mathematical optimization; Feature selection; Constraint (computer-aided design); Likelihood principle; Applied mathematics; Maximum likelihood; Statistics; Computer science; Quasi-maximum likelihood; Artificial intelligence; Estimator","retraction":null,"screen_n_in":null,"score":{"opus":0.1239338934358652,"gpt":0.4624732647641817,"spread":0.3385393713283165,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005879144,0.000118699,0.0003238894,0.00007183909,0.00008571172,0.00004595586,0.00006968522,0.00007190122,0.00006409275],"category_scores_gemma":[0.004605101,0.00008960439,0.00002529092,0.0001073417,0.00005089377,0.0001334734,0.000009218019,0.0003700431,0.000001029911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002584666,"about_ca_system_score_gemma":0.0001078611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000123794,"about_ca_topic_score_gemma":1.37647e-7,"domain_scores_codex":[0.9988467,0.000106219,0.0004529918,0.0001269136,0.000243001,0.0002241498],"domain_scores_gemma":[0.9962301,0.003095731,0.0001969511,0.00005898516,0.0001999476,0.0002182855],"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":[0.0003647291,0.0003691177,0.002942879,0.00009644335,0.00003504051,0.0001137006,0.0002611309,0.0006977329,0.001359681,0.9090949,0.005948727,0.07871588],"study_design_scores_gemma":[0.00043397,0.0009893286,0.004941099,0.0001567132,0.00005027524,0.00006185282,0.00002575586,0.03140761,0.00009374603,0.9611855,0.0005337929,0.0001203506],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004117337,0.00005824406,0.9944339,0.0002125688,0.00006099899,0.00004018838,0.00001837399,0.00001705124,0.001041287],"genre_scores_gemma":[0.3566689,0.000003489306,0.6429984,0.0002523931,0.00005715482,4.260288e-7,9.191425e-7,0.000004467383,0.00001389986],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3525515,"threshold_uncertainty_score":0.5513069,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1971921760","doi":"10.1016/s0378-3758(99)00195-0","title":"Noncanonical links in generalized linear models – when is the effort justified?","year":2000,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":30,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Mathematics; Generalized linear model; Deviance (statistics); Goodness of fit; Binomial regression; Statistics; Negative binomial distribution; Parametric statistics; Applied mathematics; Logit; Residual; Binomial distribution; Econometrics; Logistic regression; Algorithm; Poisson distribution","retraction":null,"screen_n_in":null,"score":{"opus":0.09709194964356595,"gpt":0.3976390624505003,"spread":0.3005471128069344,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009924561,0.0001843761,0.0005239731,0.00007088557,0.0001014834,0.00008432777,0.0002503585,0.0001795113,0.0007104974],"category_scores_gemma":[0.001433049,0.0001133365,0.00005353657,0.0001096132,0.0002344811,0.0001556,0.0000382412,0.001025588,0.000007331547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002607998,"about_ca_system_score_gemma":0.000130911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004647568,"about_ca_topic_score_gemma":0.000003342887,"domain_scores_codex":[0.9980905,0.0001804192,0.0008486305,0.0001896663,0.0003793013,0.000311505],"domain_scores_gemma":[0.994997,0.004313464,0.0001947568,0.0001712762,0.0001270261,0.000196535],"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":[0.000464736,0.0001791639,0.002083748,0.0001374842,0.00006809429,0.0002561244,0.003132504,0.0002718651,0.00006047196,0.8175818,0.01057847,0.1651855],"study_design_scores_gemma":[0.0006281075,0.0002465761,0.002474382,0.0002910143,0.00006256862,0.00009667816,0.00006309571,0.06001737,0.00002325584,0.9346369,0.001297906,0.0001621382],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03890398,0.0001967371,0.9563091,0.0008509037,0.0000863392,0.0001127774,0.00007712905,0.00001125072,0.00345178],"genre_scores_gemma":[0.3134204,0.0001348907,0.6855728,0.000603507,0.0001371978,0.000004216407,0.000002052554,0.00001386701,0.0001110897],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2745164,"threshold_uncertainty_score":0.7779449,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1990948848","doi":"10.1016/s0378-3758(00)00282-2","title":"Super-simple designs with v⩽32","year":2001,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"graph theory and CDMA systems","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University; University of Northern British Columbia","funders":"","keywords":"Mathematics; Simple (philosophy); Combinatorics; Set (abstract data type); Discrete mathematics; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.02859977585594852,"gpt":0.2650520114568665,"spread":0.2364522356009179,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000167973,0.00008188087,0.0001662782,0.00005439773,0.00004374777,0.0000422326,0.00005890949,0.00003230482,0.00005399708],"category_scores_gemma":[0.0000701325,0.00005748149,0.00001247719,0.0000693451,0.00005054116,0.0001262943,0.000004845295,0.0001836711,0.000003453343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000812336,"about_ca_system_score_gemma":0.00001355468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002858258,"about_ca_topic_score_gemma":8.975102e-7,"domain_scores_codex":[0.9994656,0.00002492353,0.000205271,0.00004944645,0.0001155944,0.0001391412],"domain_scores_gemma":[0.999441,0.0003135729,0.00003604965,0.00004598148,0.0000453871,0.00011796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001223158,0.0002153495,0.6205082,0.0006620095,0.0006808244,0.00514536,0.007391085,0.05931099,0.01102132,0.2050166,0.0189076,0.06991747],"study_design_scores_gemma":[0.007757473,0.008969873,0.5836774,0.003777294,0.0005481343,0.01561008,0.009254569,0.124121,0.002580127,0.1788378,0.06196907,0.002897118],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5165937,0.0003182369,0.4808358,0.000009860948,0.00006537976,0.0000201042,0.000007700698,0.00001978188,0.002129446],"genre_scores_gemma":[0.9972388,0.00004232524,0.002623634,0.00001730729,0.00005160767,6.534035e-7,0.000001461291,0.000007538117,0.00001668154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4806451,"threshold_uncertainty_score":0.2344027,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2061758728","doi":"10.1016/j.jspi.2012.02.045","title":"Optimal design and maintenance of a repairable multi-state system with standby components","year":2012,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reliability engineering; Markov model; Markov process; Mathematical optimization; State (computer science); Markov chain; Process (computing); Mathematics; Electric power system; Work (physics); Power (physics); Preventive maintenance; Reliability (semiconductor); Control theory (sociology); Computer science; Engineering; Statistics; Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.02763495094561653,"gpt":0.2504595994827245,"spread":0.222824648537108,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000414015,0.00008885584,0.0002319962,0.00004365557,0.00003204788,0.00002085505,0.00003798485,0.00003073964,0.000002232021],"category_scores_gemma":[0.0001296103,0.0000627158,0.000009854738,0.00004735237,0.00009235734,0.0002370114,0.00001032932,0.0001449129,2.970192e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002860481,"about_ca_system_score_gemma":0.00001589425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000724429,"about_ca_topic_score_gemma":1.713377e-7,"domain_scores_codex":[0.9993111,0.00003610327,0.0002988598,0.00005839013,0.0001209715,0.0001745816],"domain_scores_gemma":[0.9993415,0.0002571738,0.0001135727,0.00004912915,0.0001153854,0.0001231662],"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":[0.0004861128,0.00006924859,0.02374466,0.0007367862,0.00008560815,0.00004277854,0.001716519,0.9677255,0.001104986,0.002503132,0.0003425078,0.001442119],"study_design_scores_gemma":[0.0008790818,0.0004102748,0.02989559,0.001196723,0.00003561751,0.0001957639,0.0004886751,0.9663562,0.0002820684,0.00005921598,0.0000636239,0.0001371261],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1604003,0.0004035979,0.8389986,0.0000045473,0.00004908177,0.00005445799,0.00001486812,0.00001423591,0.00006027948],"genre_scores_gemma":[0.7457467,0.00009832686,0.2541296,0.000002906037,0.000008120916,8.979792e-7,9.85521e-7,0.000005922335,0.000006494824],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5853464,"threshold_uncertainty_score":0.2557476,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2038568847","doi":"10.1016/s0378-3758(01)00232-4","title":"How are moments and moments of spacings related to distribution functions?","year":2002,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":28,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; L-moment; Moment (physics); Random variable; Independent and identically distributed random variables; Method of moments (probability theory); Central moment; Distribution (mathematics); Moment-generating function; Range (aeronautics); Function (biology); Expression (computer science); Mathematical analysis; Distribution function; Applied mathematics; Statistics; Order statistic; Quantum mechanics","retraction":null,"screen_n_in":null,"score":{"opus":0.08884896453767013,"gpt":0.3340390328909998,"spread":0.2451900683533297,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006366555,0.000085581,0.0002651074,0.0001225942,0.00007029127,0.0001217364,0.0001012032,0.0000487168,0.00004085461],"category_scores_gemma":[0.006396777,0.0000584858,0.00001903725,0.0002242393,0.00008963126,0.0002127578,0.00003878901,0.0001647961,0.000004732624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002143774,"about_ca_system_score_gemma":0.00001061468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001787213,"about_ca_topic_score_gemma":7.791101e-8,"domain_scores_codex":[0.9987428,0.00004566278,0.000451971,0.0001378623,0.0004933858,0.0001283032],"domain_scores_gemma":[0.9981976,0.0009731386,0.0002837597,0.00008440109,0.0002675639,0.0001934981],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006353463,0.0007530035,0.565772,0.0002858033,0.0004003848,0.0004529252,0.006922607,0.03365011,0.004342459,0.05689719,0.1972963,0.1325919],"study_design_scores_gemma":[0.002092599,0.002476805,0.8115826,0.001216117,0.0001397627,0.0003483575,0.002912452,0.09944178,0.0001912075,0.07101651,0.00803157,0.0005502359],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2119571,0.0002606937,0.7868406,0.0005537524,0.0001452707,0.00004266706,0.00008903842,0.000004509177,0.0001063763],"genre_scores_gemma":[0.9959924,0.00002305635,0.003450156,0.00001762916,0.00001425559,6.218083e-7,0.000001948153,0.000002902663,0.0004970487],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7840353,"threshold_uncertainty_score":0.7658002,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2068057120","doi":"10.1016/j.jspi.2008.03.035","title":"On order statistics from bivariate skew-normal and skew- distributions","year":2008,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":27,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Skew; Bivariate analysis; Skew normal distribution; Statistics; Multivariate normal distribution; Order statistic; Covariance; Distribution (mathematics); Multivariate statistics; L-moment; Econometrics; Normal distribution; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.07544632309094416,"gpt":0.3715468287522896,"spread":0.2961005056613454,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001686051,0.000157184,0.0003094472,0.00006422921,0.0003067102,0.00006176718,0.00009002985,0.0001012369,0.0003339491],"category_scores_gemma":[0.005453476,0.0001298587,0.00001956291,0.0001257719,0.0003075891,0.0001143947,0.00003594,0.0004774158,0.00001606363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000284471,"about_ca_system_score_gemma":0.0001008411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002379414,"about_ca_topic_score_gemma":0.00000114282,"domain_scores_codex":[0.9986938,0.00006539062,0.0005757739,0.0001618415,0.0003054368,0.0001978157],"domain_scores_gemma":[0.9942204,0.004789545,0.000271733,0.0001097309,0.0003244121,0.0002842172],"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":[0.00004767799,0.000118154,0.001311836,0.00001778222,0.00003144081,0.00004755917,0.000182204,0.00001088796,0.00003470708,0.9846192,0.01184084,0.001737733],"study_design_scores_gemma":[0.0006637909,0.0002469078,0.1268146,0.0001105658,0.00007727073,0.0001044613,0.00004125241,0.006951541,0.00002941079,0.8641852,0.0005960995,0.0001789162],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04456702,0.00005035746,0.9504321,0.0002488134,0.00006160199,0.00006404846,0.004093452,0.00002010215,0.0004625541],"genre_scores_gemma":[0.7292074,0.00004936634,0.2704039,0.0001057518,0.0000452099,0.000003444644,0.0001437809,0.000007937099,0.00003319752],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6846404,"threshold_uncertainty_score":0.6528714,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2048687076","doi":"10.1016/s0378-3758(99)00114-7","title":"Perfect Mendelsohn designs with block size six","year":2000,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"graph theory and CDMA systems","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Mount Saint Vincent University","funders":"Natural Sciences and Engineering Research Council of Canada; Mount Saint Vincent University; National Science Foundation","keywords":"Mod; Mathematics; Combinatorics; Block (permutation group theory); Block design; Discrete mathematics; Arithmetic; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.01586154293082328,"gpt":0.2439174049004188,"spread":0.2280558619695955,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000202848,0.0001046041,0.0002062283,0.00003578164,0.00005396441,0.00004832928,0.0000675712,0.00004057366,0.0002329754],"category_scores_gemma":[0.00006821119,0.00007519592,0.00001777383,0.00006474816,0.00005824893,0.0001139511,0.000003235001,0.000241907,0.000007741466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001002878,"about_ca_system_score_gemma":0.00001727768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002808204,"about_ca_topic_score_gemma":4.530269e-7,"domain_scores_codex":[0.999355,0.00004104606,0.0002386563,0.00006538998,0.000143459,0.0001564846],"domain_scores_gemma":[0.9991269,0.0006122388,0.00003896404,0.00005350116,0.00003638308,0.0001320733],"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":[0.004238267,0.0005679745,0.1205059,0.001756791,0.002199223,0.006004818,0.01893574,0.4125296,0.02156824,0.1135633,0.02722326,0.2709068],"study_design_scores_gemma":[0.01432304,0.01985494,0.5700406,0.009581932,0.001408323,0.01748058,0.005406171,0.2008553,0.006201897,0.1100018,0.03946101,0.005384374],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9451696,0.000522413,0.04469234,0.00001777042,0.00009214934,0.0000451642,0.00001852148,0.00003982749,0.009402274],"genre_scores_gemma":[0.9968506,0.00004748389,0.00295871,0.00001976039,0.00005487373,9.011779e-7,5.786862e-7,0.000009564928,0.00005752552],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4495347,"threshold_uncertainty_score":0.3066401,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2059402501","doi":"10.1016/j.jspi.2008.01.004","title":"Detection of outliers in multilevel models","year":2008,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":26,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Outlier; Anomaly detection; Mathematics; Statistics; Multilevel model; Pattern recognition (psychology); Data mining; Artificial intelligence; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.1935916049167646,"gpt":0.4041009118649649,"spread":0.2105093069482004,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000483653,0.0001006878,0.0003850761,0.0001343988,0.00004129434,0.000008920031,0.00008246877,0.00006677908,0.00001989563],"category_scores_gemma":[0.00508131,0.00007881129,0.00002593282,0.00008588852,0.0001835863,0.0001224129,0.00002311377,0.0003142993,5.154843e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002049048,"about_ca_system_score_gemma":0.00006317264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002635284,"about_ca_topic_score_gemma":0.000001350283,"domain_scores_codex":[0.9987506,0.00009717818,0.0006568629,0.0000979986,0.0002436653,0.0001537476],"domain_scores_gemma":[0.9960225,0.003333134,0.0002878145,0.00006877468,0.0001755729,0.0001122592],"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":[0.0008378781,0.0006347233,0.04181293,0.0005717993,0.0001049441,0.0006499868,0.008586317,0.001489923,0.007837908,0.7570607,0.0004785846,0.1799343],"study_design_scores_gemma":[0.0008312192,0.0006151361,0.0813862,0.0004021997,0.00002921705,0.0001801704,0.0002916411,0.08607277,0.0008983102,0.8291145,0.00001568894,0.0001629385],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.273778,0.00006625127,0.7256034,0.000009312525,0.0000542984,0.00003185285,0.00001962564,0.00000363021,0.0004335993],"genre_scores_gemma":[0.7310957,0.00003899924,0.2688237,0.00001195251,0.00001616195,7.583171e-7,2.446959e-7,0.000004832502,0.000007627403],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4573177,"threshold_uncertainty_score":0.608317,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2089610455","doi":"10.1016/j.jspi.2009.05.018","title":"Order statistics from trivariate normal and -distributions in terms of generalized skew-normal and skew- distributions","year":2009,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":23,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Skew; Skew normal distribution; Order statistic; Skewness; Generalization; Noncentral chi-squared distribution; Multivariate normal distribution; Distribution (mathematics); Statistics; Multivariate statistics; Univariate; Bivariate analysis; Generalized integer gamma distribution; Normal distribution; Applied mathematics; Mathematical analysis; Ratio distribution; Asymptotic distribution","retraction":null,"screen_n_in":null,"score":{"opus":0.04772421294470709,"gpt":0.3675622493727398,"spread":0.3198380364280327,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003022707,0.0001748581,0.0004671923,0.00009771975,0.000150982,0.00007957941,0.00009365538,0.0001268441,0.0001252864],"category_scores_gemma":[0.003275608,0.0001526315,0.00002238388,0.0001983062,0.0002795214,0.0001776168,0.0000402638,0.0004275253,0.000001239553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003244822,"about_ca_system_score_gemma":0.00007455803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004923761,"about_ca_topic_score_gemma":0.000006247527,"domain_scores_codex":[0.9983354,0.00009039616,0.0009128012,0.0001763365,0.000250755,0.0002343172],"domain_scores_gemma":[0.9969994,0.002008053,0.0003839802,0.0001098446,0.0002457218,0.0002530447],"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":[0.00007890959,0.0002175368,0.005407197,0.000034897,0.00002596696,0.00002235651,0.0001883053,0.00001185824,0.0003712064,0.9867736,0.001233135,0.005635097],"study_design_scores_gemma":[0.001166223,0.0002442232,0.3588688,0.0001361521,0.00009614341,0.00004048065,0.00003945894,0.01045359,0.00008295805,0.6285664,0.0001509517,0.0001546053],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1056703,0.0000808414,0.885795,0.0003665271,0.00003029351,0.00009627301,0.007772052,0.00001093394,0.0001777691],"genre_scores_gemma":[0.7461932,0.00007758035,0.2533507,0.00004042545,0.00002559831,0.000003146857,0.0002961982,0.000004671198,0.000008465008],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6405229,"threshold_uncertainty_score":0.6224134,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2028387228","doi":"10.1016/j.jspi.2011.12.019","title":"Generalized minimum aberration two-level split-plot designs","year":2012,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Mathematics; Plot (graphics); Split plot; Restricted randomization; Rank (graph theory); Algorithm; Combinatorics; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.4141405124931503,"gpt":0.5156379488757189,"spread":0.1014974363825686,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004113166,0.0001484323,0.0003950872,0.0001865736,0.0001263096,0.0002494407,0.0002640119,0.00006521169,0.0003595029],"category_scores_gemma":[0.006694321,0.0001015107,0.00004914579,0.0002072011,0.0001599837,0.0007918997,0.00006201559,0.0002646924,0.00004386842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003426352,"about_ca_system_score_gemma":0.00008200014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001138613,"about_ca_topic_score_gemma":2.866677e-7,"domain_scores_codex":[0.9971572,0.000510104,0.0009090185,0.0001709136,0.0009453924,0.0003074253],"domain_scores_gemma":[0.994597,0.004095088,0.0004598285,0.0001448335,0.0003056404,0.0003976159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.001673285,0.0007294438,0.1870483,0.00003629632,0.0001672538,0.0002010963,0.01075945,0.001851684,0.2132855,0.356858,0.03424234,0.1931473],"study_design_scores_gemma":[0.005178347,0.003171719,0.6788901,0.0003807613,0.0002037504,0.001090065,0.004282638,0.06548019,0.01791205,0.2157741,0.006320147,0.001316095],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2071784,0.0006049532,0.7901008,0.0000832864,0.0004277487,0.00005090718,0.00002280586,0.000007196596,0.001523883],"genre_scores_gemma":[0.5930748,0.000007895238,0.406513,0.0001210937,0.0001402255,9.907667e-7,0.000001293005,0.000005486648,0.0001351797],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4918418,"threshold_uncertainty_score":0.801421,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2087870069","doi":"10.1016/j.jspi.2014.01.005","title":"New optimal design criteria for regression models with asymmetric errors","year":2014,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Statistics; Regression; Regression analysis; Econometrics; Applied mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.2532434680156384,"gpt":0.491720987300366,"spread":0.2384775192847276,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003949828,0.0001634228,0.00046344,0.0003147057,0.0001253189,0.0003194616,0.000334789,0.00007266513,0.00006181084],"category_scores_gemma":[0.008155651,0.00009261876,0.00004162717,0.0003109367,0.0001094548,0.0005906408,0.00004931992,0.0002181054,0.000003618655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002156031,"about_ca_system_score_gemma":0.0001395269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006301077,"about_ca_topic_score_gemma":8.168958e-8,"domain_scores_codex":[0.9975662,0.0003938534,0.0007044003,0.0002567519,0.00083925,0.0002395162],"domain_scores_gemma":[0.9888809,0.009731909,0.0004675888,0.000150816,0.0003948542,0.0003739471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007475519,0.0001992089,0.003148452,0.00004925625,0.0000990331,0.0001308352,0.002957353,0.09402903,0.00758198,0.1143414,0.06614708,0.7038408],"study_design_scores_gemma":[0.001738309,0.006049227,0.003988934,0.0003470619,0.0000537425,0.0002029067,0.0005951745,0.7820947,0.002303467,0.2012655,0.001040669,0.0003203636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004185024,0.0002388394,0.9943968,0.0001105852,0.0001565756,0.00009773414,0.00001027904,0.000007791012,0.0007963623],"genre_scores_gemma":[0.4091864,0.000004017319,0.5906046,0.00005301863,0.00005892122,0.000001179413,5.403183e-7,0.000006757833,0.00008457067],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7035205,"threshold_uncertainty_score":0.9763666,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2076449511","doi":"10.1016/j.jspi.2008.11.017","title":"On consistency, natural restrictions and estimability under classical and extended growth curve models","year":2009,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Mathematics; Consistency (knowledge bases); Estimator; Applied mathematics; Growth curve (statistics); Matrix (chemical analysis); Statistics; Discrete mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.02869408861701279,"gpt":0.3067868434325413,"spread":0.2780927548155285,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003348351,0.0001070643,0.0002156766,0.00007595475,0.0001580496,0.0001623753,0.0001152831,0.00004764093,0.000002142584],"category_scores_gemma":[0.0005733582,0.00007834029,0.00001731041,0.00008681956,0.0001983308,0.0004076017,0.00004314607,0.0003978673,3.520364e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001359741,"about_ca_system_score_gemma":0.0000599238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003537455,"about_ca_topic_score_gemma":2.218986e-7,"domain_scores_codex":[0.9991107,0.00009584731,0.0002725173,0.0001852155,0.0001873068,0.0001483923],"domain_scores_gemma":[0.9980654,0.001445891,0.0001072969,0.00008641676,0.000108289,0.0001867797],"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":[0.00004550754,0.00005761149,0.0002360571,0.000008427037,0.000007637207,0.00005040567,0.000131024,0.0001449872,0.00002272625,0.9831001,0.0001393057,0.01605618],"study_design_scores_gemma":[0.0002800855,0.0006136255,0.06320874,0.00006612828,0.00001088888,0.0002287994,0.00002585603,0.1769605,0.000006656509,0.7585077,0.000005358524,0.00008561413],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05730716,0.0003794127,0.9402197,0.001134797,0.00009854284,0.00003535467,0.000008204188,0.00001634057,0.0008005037],"genre_scores_gemma":[0.9439875,0.00004612702,0.05567105,0.0002551507,0.00002627841,2.850258e-7,5.190934e-7,0.000001641556,0.0000113683],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8866804,"threshold_uncertainty_score":0.3194624,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2034258392","doi":"10.1016/j.jspi.2008.05.023","title":"A case–control study relating railroad worker mortality to diesel exhaust exposure using a threshold regression model","year":2008,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"National Institute for Occupational Safety and Health; National Cancer Institute","keywords":"Lung cancer; Medicine; Proportional hazards model; Demography; Environmental health; Diesel exhaust; Regression analysis; Survival analysis; Gerontology; Diesel engine; Surgery; Statistics; Internal medicine; Engineering; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.1812472438897178,"gpt":0.4040478556079523,"spread":0.2228006117182345,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001057717,0.0001576722,0.0003569509,0.00005080087,0.0004766893,0.00003957843,0.0001016691,0.00007532919,0.0001015791],"category_scores_gemma":[0.0008626742,0.0001146894,0.00002724733,0.0001306981,0.0001471601,0.0003507207,0.00009029143,0.0004961772,0.000005570744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009166443,"about_ca_system_score_gemma":0.00006352369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001684857,"about_ca_topic_score_gemma":0.00001752497,"domain_scores_codex":[0.9982265,0.0001312314,0.0006357857,0.0002022395,0.0004804129,0.0003238401],"domain_scores_gemma":[0.9986442,0.0004222898,0.000289169,0.0001302627,0.00003737514,0.0004767201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000245499,0.0001813066,0.8933943,0.00001917056,0.00002972755,0.003405631,0.01086494,0.08730756,0.0001226496,0.00009212898,0.0009607994,0.003376302],"study_design_scores_gemma":[0.001104174,0.001072346,0.6940142,0.0003034325,0.0000771326,0.001927884,0.001900399,0.2982666,0.000004365692,0.001083257,0.00001702128,0.0002291766],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8092631,0.00006938678,0.1901039,0.00009095691,0.0000415309,0.0001385394,0.00002257945,0.000007926902,0.0002620675],"genre_scores_gemma":[0.9763594,0.000008245412,0.0230557,0.000487892,0.00004917823,0.000001750258,3.739684e-7,0.000008189017,0.00002922128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2109591,"threshold_uncertainty_score":0.4676897,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2073560153","doi":"10.1016/j.jspi.2010.02.013","title":"Simultaneous closeness among order statistics to population quantiles","year":2010,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":21,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba; McMaster University","funders":"","keywords":"Mathematics; Order statistic; Statistics; Quantile; Percentile; Closeness; Scale parameter; Location parameter; Statistic; Population; Sample size determination; Probability distribution; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.04446570098326926,"gpt":0.4008182634579735,"spread":0.3563525624747043,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0002827119,0.0001288271,0.0002672695,0.0000905996,0.0001379422,0.00009882081,0.0001108396,0.00007742886,0.0002003285],"category_scores_gemma":[0.01408385,0.0001075663,0.00001702977,0.0001638244,0.0001186853,0.0001076514,0.00002775468,0.0003687075,0.00001251448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001585355,"about_ca_system_score_gemma":0.00005103839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002539807,"about_ca_topic_score_gemma":0.00001845436,"domain_scores_codex":[0.9987533,0.00004070218,0.0005896313,0.0001350583,0.0003034403,0.0001778834],"domain_scores_gemma":[0.9944692,0.004342061,0.0002631945,0.0001112757,0.0005207525,0.0002935001],"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":[0.00003564306,0.00008401676,0.01009591,0.00004470487,0.00001431404,0.00003383998,0.0001580521,0.0003172792,0.0003576009,0.9765574,0.002215842,0.01008535],"study_design_scores_gemma":[0.0005413385,0.0002946058,0.3682768,0.0001522178,0.0000929204,0.0001018082,0.0001988879,0.08432538,0.00008564431,0.5446559,0.0009135825,0.0003609585],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2378843,0.000004052953,0.7612473,0.0001038244,0.0001139405,0.00007772475,0.000416618,0.00001738027,0.0001348838],"genre_scores_gemma":[0.7182717,0.000001863595,0.2815494,0.00005346142,0.00005124017,0.00000280319,0.00003609771,0.000008044987,0.00002542173],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4803874,"threshold_uncertainty_score":0.9942209,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2082939789","doi":"10.1016/s0378-3758(00)00227-5","title":"Sample size determination in step-down and step-up multiple tests for comparing treatments with a control","year":2001,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":19,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Mathematics; Sample size determination; Statistics; Sample (material); Multiple comparisons problem; Econometrics; Chromatography","retraction":null,"screen_n_in":null,"score":{"opus":0.4017376160477892,"gpt":0.53015615459137,"spread":0.1284185385435808,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001178091,0.0001584305,0.0006903982,0.00007363193,0.00006962761,0.00007183717,0.00007714218,0.0000775098,0.00001801361],"category_scores_gemma":[0.1136952,0.0001120479,0.00002560897,0.00007537814,0.0001413677,0.0001197868,0.00002089324,0.0002397852,2.739909e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003873534,"about_ca_system_score_gemma":0.00004582963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002580644,"about_ca_topic_score_gemma":0.00002174481,"domain_scores_codex":[0.9983451,0.0002108052,0.0007959534,0.0001817381,0.0002321675,0.0002342726],"domain_scores_gemma":[0.8481998,0.1510477,0.000362125,0.00007482494,0.000156899,0.0001586264],"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":[0.004046541,0.0003902701,0.7813655,0.0002810939,0.0001394359,0.0001985569,0.0004773924,0.00002769318,0.0001451014,0.01964517,0.0002155949,0.1930677],"study_design_scores_gemma":[0.01581028,0.003005176,0.404585,0.001110061,0.0003155941,0.0001608908,0.0002741593,0.1568108,0.00002330235,0.4175153,0.00008633566,0.0003030707],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2130745,0.00003371571,0.7863916,0.00004864774,0.00006392445,0.0002357859,0.0001082692,0.000007166785,0.00003641503],"genre_scores_gemma":[0.5167739,0.00001340517,0.4831339,0.00002513969,0.00003207082,0.000007581639,6.024672e-7,0.000007061014,0.000006342185],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3978701,"threshold_uncertainty_score":0.8937705,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2010720561","doi":"10.1016/j.jspi.2010.06.011","title":"A random-sum Wilcoxon statistic and its application to analysis of ROC and LROC data","year":2010,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":18,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"National Cancer Institute","keywords":"Wilcoxon signed-rank test; Mathematics; Scan statistic; Statistic; Statistics; Rank (graph theory); Ancillary statistic; Test statistic; Sample size determination; Mann–Whitney U test; Statistical hypothesis testing; Combinatorics","retraction":null,"screen_n_in":null,"score":{"opus":0.1011320078938469,"gpt":0.4362104964558866,"spread":0.3350784885620396,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001188449,0.0001578893,0.0006932994,0.0002431039,0.00007602551,0.00006565749,0.0002030513,0.00007992125,0.00005226523],"category_scores_gemma":[0.01352706,0.0001219198,0.00001994711,0.0002740214,0.0001524074,0.0001499689,0.0001533028,0.000374165,7.516634e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006052749,"about_ca_system_score_gemma":0.00005375944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002133141,"about_ca_topic_score_gemma":0.00001677105,"domain_scores_codex":[0.998416,0.0001039814,0.000725301,0.0002645979,0.0003034954,0.0001865887],"domain_scores_gemma":[0.9914564,0.007312024,0.0003926823,0.0002345203,0.0002821526,0.0003221718],"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":[0.0007945772,0.000225657,0.03441674,0.000633539,0.0008097452,0.00005346556,0.001671832,0.00005338548,0.01373908,0.7880281,0.001002033,0.1585718],"study_design_scores_gemma":[0.002338438,0.001221819,0.3054723,0.0004522862,0.003275218,0.0001309228,0.0004120399,0.3256293,0.0003139152,0.3595524,0.0006054128,0.0005959852],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2101521,0.0001395608,0.7888029,0.00008021669,0.00004486453,0.0001058709,0.0005650776,0.000005757568,0.0001036992],"genre_scores_gemma":[0.6977414,0.00005316777,0.30211,0.00003958007,0.00002796214,0.000002399486,0.00001238869,0.000006595496,0.000006438051],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4875894,"threshold_uncertainty_score":0.9947824,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2038336950","doi":"10.1016/j.jspi.2008.05.022","title":"Robust designs for misspecified logistic models","year":2008,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Mathematics; Statistics; Logistic regression; Econometrics; Applied mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.7552309551786061,"gpt":0.5199634607146267,"spread":0.2352674944639793,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00206897,0.0001326934,0.0004282441,0.0001683652,0.000189734,0.0001320693,0.0003289576,0.00006818544,0.0001008572],"category_scores_gemma":[0.009610993,0.00009109046,0.00006010709,0.0001602906,0.0003026346,0.0003782241,0.0000435413,0.0002188952,0.000007639567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002664705,"about_ca_system_score_gemma":0.0001277355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003997687,"about_ca_topic_score_gemma":1.085064e-7,"domain_scores_codex":[0.9977995,0.0001972187,0.0008334528,0.000224209,0.0007162626,0.0002293287],"domain_scores_gemma":[0.9889098,0.009849969,0.0003693377,0.0001359139,0.0004733129,0.0002616271],"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":[0.004683016,0.0007405368,0.01651424,0.00008348551,0.0002005448,0.001878777,0.008037958,0.2457345,0.0164053,0.4869777,0.1168553,0.1018886],"study_design_scores_gemma":[0.001627016,0.00253261,0.01572461,0.0001640649,0.00004835043,0.0008943221,0.001147226,0.3880327,0.0009888103,0.5868372,0.001575241,0.0004278675],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00961722,0.0005439432,0.9874043,0.00007592433,0.0001824873,0.00008181318,0.0000360889,0.000007403923,0.002050804],"genre_scores_gemma":[0.5389971,0.00002595356,0.4607072,0.00007080587,0.00005613948,0.000001476426,8.029173e-7,0.000005227242,0.0001352438],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5293799,"threshold_uncertainty_score":0.9987315,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2037147413","doi":"10.1016/j.jspi.2004.12.002","title":"Predictive inference for future responses given a doubly censored sample from a two parameter exponential distribution","year":2005,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":18,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Inference; Statistics; Exponential distribution; Exponential function; Statistical inference; Sample (material); Posterior predictive distribution; Applied mathematics; Exponential family; Distribution (mathematics); Econometrics; Bayesian inference; Mathematical analysis; Bayesian probability; Computer science; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.07063875939026323,"gpt":0.4043396984261214,"spread":0.3337009390358582,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0002773571,0.0001559842,0.0003348057,0.00004956807,0.0001699107,0.0001043735,0.0001222225,0.00008500811,0.0001280137],"category_scores_gemma":[0.01044201,0.0001287578,0.00005505675,0.00008762454,0.0001566494,0.0002060309,0.00002853734,0.0002664802,0.000004458408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006170868,"about_ca_system_score_gemma":0.00009229946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001470585,"about_ca_topic_score_gemma":0.000002243167,"domain_scores_codex":[0.9985976,0.00009459264,0.0006362524,0.0001840816,0.0002750703,0.0002123863],"domain_scores_gemma":[0.9861208,0.01280136,0.0003650825,0.0001101925,0.0003850777,0.0002174476],"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":[0.001708903,0.0002587896,0.007313021,0.00007009407,0.0001590194,0.00001067868,0.00116571,0.0002556227,0.0003033692,0.9384174,0.01048217,0.03985522],"study_design_scores_gemma":[0.0031339,0.0007085162,0.1591637,0.0002964364,0.000342046,0.00002330571,0.0005676105,0.06955446,0.0003774984,0.7570052,0.008438594,0.0003887462],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08238213,0.00005160396,0.9029533,0.0007180318,0.00006571953,0.0001619837,0.01362294,0.00002412898,0.00002020918],"genre_scores_gemma":[0.7664692,0.00001112525,0.2326533,0.00004453453,0.0003457981,0.00001577337,0.0004455532,0.000006995127,0.000007704708],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6840871,"threshold_uncertainty_score":0.9978935,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2089904831","doi":"10.1016/j.jspi.2003.12.021","title":"Computation of distribution functions from likelihood information near observed data","year":2004,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":18,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University; University of Toronto","funders":"","keywords":"Mathematics; Computation; Distribution (mathematics); Statistics; Applied mathematics; Econometrics; Statistical physics; Algorithm; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.1304267517445008,"gpt":0.3863378398456862,"spread":0.2559110881011854,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004888814,0.0001060551,0.0003098868,0.00004126263,0.0000918928,0.00009376036,0.0001570575,0.00006883986,0.00002783111],"category_scores_gemma":[0.005840601,0.00008538635,0.00002144129,0.0001139744,0.0001418995,0.0006094729,0.00006784878,0.0002521094,0.000003665109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003037248,"about_ca_system_score_gemma":0.000164788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008867287,"about_ca_topic_score_gemma":0.000002409348,"domain_scores_codex":[0.9986349,0.00007674997,0.0007570364,0.00010137,0.0002936861,0.0001361949],"domain_scores_gemma":[0.9969145,0.001966806,0.0005179025,0.0001451756,0.0003281233,0.0001274774],"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":[0.0004939676,0.0004651322,0.01443752,0.0004615254,0.0002227119,0.00004747025,0.002007257,0.0005956671,0.0004196563,0.6996626,0.004287114,0.2768994],"study_design_scores_gemma":[0.0008546262,0.0004244211,0.07979345,0.0005261997,0.000128078,0.00002140287,0.000294059,0.01473504,0.00006357408,0.9028711,0.0001606321,0.0001273953],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04861091,0.0000554507,0.9491898,0.0001024885,0.0001330181,0.00005317249,0.00176954,0.00001046521,0.0000751591],"genre_scores_gemma":[0.5516765,0.000008514683,0.4480587,0.00001597417,0.00002824291,4.197889e-7,0.0002088312,0.000002637293,2.949777e-7],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5030655,"threshold_uncertainty_score":0.6992167,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1985741712","doi":"10.1016/s0378-3758(01)00096-9","title":"The distribution of Hermitian quadratic forms in elliptically contoured random vectors","year":2002,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Hermitian matrix; Quadratic equation; Distribution (mathematics); Mathematical analysis; Combinatorics; Pure mathematics; Geometry","retraction":null,"screen_n_in":null,"score":{"opus":0.02226225586573233,"gpt":0.2902068264556805,"spread":0.2679445705899482,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007674097,0.00008042021,0.0002470108,0.00003659376,0.00007129864,0.00009108736,0.0002281931,0.00004513317,0.000005249478],"category_scores_gemma":[0.0009791112,0.00004663604,0.0000302715,0.0001122486,0.0001160002,0.0002100802,0.00002956745,0.0002483496,6.221147e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000161061,"about_ca_system_score_gemma":0.00003143315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000604489,"about_ca_topic_score_gemma":0.000002371195,"domain_scores_codex":[0.9989122,0.0001331121,0.0004870634,0.00008980807,0.0002081581,0.0001696947],"domain_scores_gemma":[0.9978148,0.001678227,0.0002027125,0.0001001473,0.0001024295,0.0001016915],"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":[0.0001308809,0.0001007693,0.00421874,0.00004495557,0.0000321061,0.0001278175,0.00132928,0.0001230867,0.0002619644,0.7030635,0.00106838,0.2894985],"study_design_scores_gemma":[0.003284954,0.001264183,0.09608762,0.0006589636,0.00004175729,0.0002211047,0.00009780157,0.4404475,0.000242494,0.4564919,0.0008415924,0.0003200748],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01641408,0.0007123341,0.9819888,0.0003897855,0.00008783116,0.00004460827,0.000006333437,0.000003813101,0.0003524284],"genre_scores_gemma":[0.9491798,0.0001268799,0.05061972,0.0000338202,0.00002274971,8.223146e-7,6.555372e-7,0.000002078445,0.00001350474],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9327657,"threshold_uncertainty_score":0.1901762,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1491894411","doi":"10.1016/s0378-3758(02)00204-5","title":"Block disjoint difference families for Steiner triple systems:","year":2002,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"graph theory and CDMA systems","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Disjoint sets; Mathematics; Block (permutation group theory); Combinatorics; Steiner system; Discrete mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.02586367156979995,"gpt":0.2446282121276711,"spread":0.2187645405578711,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002004564,0.0001269371,0.0003114357,0.00009251525,0.00006460379,0.00007841208,0.00009109563,0.00005604957,0.00001367641],"category_scores_gemma":[0.0002305596,0.00009494439,0.00003592716,0.00006418806,0.00005853763,0.00009332843,0.00000931378,0.0001838163,0.000003091228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001403398,"about_ca_system_score_gemma":0.00000565795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000301981,"about_ca_topic_score_gemma":3.182288e-7,"domain_scores_codex":[0.9991263,0.00003378081,0.0004295779,0.00008102061,0.0001435269,0.0001857654],"domain_scores_gemma":[0.9990467,0.0005849536,0.00009052082,0.0000708605,0.00007946338,0.0001275267],"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":[0.0007401091,0.0005981014,0.046478,0.007953073,0.001422305,0.0006109214,0.01659783,0.08332793,0.02107555,0.6365231,0.08731865,0.09735446],"study_design_scores_gemma":[0.003850982,0.002504535,0.03322484,0.003138447,0.0002854518,0.0008442223,0.003941677,0.909575,0.0005450909,0.02075739,0.02007401,0.001258369],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4405921,0.00547495,0.5505157,0.00003093988,0.00111135,0.0001831272,0.0001646221,0.00006405642,0.001863165],"genre_scores_gemma":[0.998446,0.0001258763,0.001144341,0.00001050031,0.0001102272,0.000006308597,0.000001808255,0.00001083529,0.0001441283],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.826247,"threshold_uncertainty_score":0.387172,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3040840557","doi":"10.1016/j.jspi.2020.07.001","title":"Projection pursuit based tests of normality with functional data","year":2020,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":17,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Projection pursuit; Functional principal component analysis; Normality; Principal component analysis; Projection (relational algebra); Test statistic; Mathematics; Functional data analysis; Random projection; Linear subspace; Gaussian; Multivariate normal distribution; Statistical hypothesis testing; Asymptotic distribution; Multivariate statistics; Data mining; Raw data; Artificial intelligence; Computer science; Pattern recognition (psychology); Algorithm; Statistics; Estimator","retraction":null,"screen_n_in":null,"score":{"opus":0.3155827924993062,"gpt":0.4284971281068665,"spread":0.1129143356075603,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0006548858,0.0001137494,0.00034469,0.00004438676,0.00004984516,0.0000403659,0.000186614,0.00004676918,0.0001286962],"category_scores_gemma":[0.009336573,0.00007685561,0.00001551421,0.0001328917,0.000172782,0.0001707594,0.00006239425,0.0003142433,9.184739e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009926902,"about_ca_system_score_gemma":0.0002007658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009654312,"about_ca_topic_score_gemma":0.000001126512,"domain_scores_codex":[0.9986428,0.0001111072,0.0005155992,0.0001635573,0.0004324772,0.0001344821],"domain_scores_gemma":[0.9952815,0.003698754,0.0003830052,0.0001375756,0.0003137336,0.0001854515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.004919004,0.0009401813,0.2766088,0.002783662,0.0003932143,0.0003735585,0.001446386,0.0004905934,0.004301274,0.5784672,0.02127871,0.1079974],"study_design_scores_gemma":[0.003314198,0.007462835,0.6270571,0.001417687,0.000523158,0.0002376474,0.0005730523,0.1737239,0.0007736119,0.183305,0.0009739106,0.0006379138],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02833667,0.00003316819,0.9705253,0.000312421,0.00004680515,0.00006125087,0.000237693,0.000009746215,0.0004369273],"genre_scores_gemma":[0.6081167,0.000002606852,0.3917066,0.0001012326,0.00005623977,6.300382e-7,0.000008481379,0.000005003951,0.000002511734],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.57978,"threshold_uncertainty_score":0.9990082,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1973360772","doi":"10.1016/j.jspi.2009.02.010","title":"De-aliasing effects using semifoldover techniques","year":2009,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Factor (programming language); Aliasing; Factorial experiment; Fractional factorial design; Factorial; Plackett–Burman design; Design of experiments; Statistics; Arithmetic; Computer science; Programming language; Artificial intelligence; Response surface methodology","retraction":null,"screen_n_in":null,"score":{"opus":0.1496450414730653,"gpt":0.5156544275279231,"spread":0.3660093860548579,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002429567,0.000111078,0.0003246697,0.0001783847,0.00009545842,0.0003316773,0.0002090674,0.00006613702,0.00003609438],"category_scores_gemma":[0.007480277,0.00007718079,0.0000387744,0.0001817443,0.0001000365,0.0003977224,0.000034763,0.0002553272,0.0000021319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000457459,"about_ca_system_score_gemma":0.00007614173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005339027,"about_ca_topic_score_gemma":2.432618e-8,"domain_scores_codex":[0.998195,0.0002941781,0.0005484234,0.0001488803,0.000613885,0.000199623],"domain_scores_gemma":[0.9953499,0.003868616,0.0003108087,0.00009703294,0.0001839426,0.0001896968],"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":[0.0003233468,0.0001391876,0.02834294,0.00002221959,0.00002871712,0.0007121676,0.001696035,0.0005837266,0.3345441,0.02538382,0.00311014,0.6051136],"study_design_scores_gemma":[0.0009301426,0.00428151,0.2158614,0.001465337,0.0001066363,0.001737443,0.00100559,0.06356848,0.1216142,0.5869138,0.001815301,0.0007000875],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1685237,0.0004279309,0.8294976,0.00005659564,0.00008332863,0.00003557093,0.000003253766,0.0000104291,0.001361515],"genre_scores_gemma":[0.5712636,0.000005673769,0.4284505,0.0002187792,0.00004493271,1.140234e-7,9.599745e-8,0.000002575562,0.00001378797],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6044135,"threshold_uncertainty_score":0.8955131,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2062901232","doi":"10.1016/j.jspi.2004.09.016","title":"Cochran's statistical theorem revisited","year":2004,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Control Systems and Identification","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University; University of Alberta","funders":"","keywords":"Mathematics; Matrix (chemical analysis); Statistics; Combinatorics; Applied mathematics; Calculus (dental); Mathematical economics; Discrete mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01241638318771067,"gpt":0.2716962464030892,"spread":0.2592798632153785,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002601657,0.00008747079,0.0002243246,0.00006505541,0.00004277542,0.00008364056,0.00006342162,0.00004284144,0.00003988546],"category_scores_gemma":[0.000400246,0.00007006711,0.0000175247,0.00005727722,0.00005423039,0.000129331,0.00000775119,0.000209545,0.000009821515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003192704,"about_ca_system_score_gemma":0.00002609047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008817978,"about_ca_topic_score_gemma":6.570934e-7,"domain_scores_codex":[0.9992152,0.00002302713,0.0003890555,0.00006983607,0.0001723546,0.0001304997],"domain_scores_gemma":[0.9993222,0.000317291,0.00007525057,0.00006213094,0.00009669198,0.0001264702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001876103,0.00009685739,0.006028,0.0005641056,0.0002409585,0.0004754218,0.001458956,0.01989746,0.01098415,0.893122,0.007653889,0.0592906],"study_design_scores_gemma":[0.006842833,0.001544158,0.5875887,0.003781755,0.0004436073,0.001186529,0.0007799575,0.08829764,0.0008024035,0.2962656,0.01118698,0.001279828],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04581725,0.001163946,0.9516082,0.0000522305,0.0001778891,0.00004326263,0.00005314156,0.0000264614,0.001057553],"genre_scores_gemma":[0.9932051,0.00007503238,0.00657548,0.00001959966,0.00009986067,8.290024e-7,0.000007469876,0.000008045713,0.000008613915],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9473878,"threshold_uncertainty_score":0.2857254,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2105936640","doi":"10.1016/j.jspi.2007.05.025","title":"Robust prediction and extrapolation designs for misspecified generalized linear regression models","year":2007,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"University of Victoria","keywords":"Extrapolation; Mathematics; Regression; Linear regression; Nonlinear regression; Regression analysis; Minimax; Robust regression; Linear model; Applied mathematics; Statistics; Proper linear model; Nonlinear system; Econometrics; Bayesian multivariate linear regression; Mathematical optimization","retraction":null,"screen_n_in":null,"score":{"opus":0.4744853354485605,"gpt":0.5029415616939009,"spread":0.02845622624534039,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004271141,0.0001108962,0.0002800971,0.0001966588,0.0001480931,0.0001386045,0.0001141856,0.00008833087,0.00002804445],"category_scores_gemma":[0.003154815,0.00007390929,0.00003217106,0.0001284432,0.0001116216,0.0004867715,0.0000265172,0.0001724054,6.156636e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002305625,"about_ca_system_score_gemma":0.00003972725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003487827,"about_ca_topic_score_gemma":2.094364e-7,"domain_scores_codex":[0.9981437,0.0001507525,0.000779573,0.000200552,0.0005544239,0.0001709951],"domain_scores_gemma":[0.9945848,0.004393363,0.0003717653,0.00008411218,0.0003490998,0.0002168712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01174371,0.0004028683,0.03589918,0.00009904012,0.0001329557,0.0002124942,0.007570507,0.1970496,0.1354922,0.1570897,0.01442334,0.4398845],"study_design_scores_gemma":[0.001188497,0.0009809583,0.02139867,0.000149542,0.0000287188,0.00009874376,0.0005545599,0.8118764,0.001698761,0.1614998,0.000382082,0.0001433524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06913182,0.000548011,0.9296504,0.00004893747,0.0001453267,0.0000945948,0.00002834748,0.000007242284,0.0003453715],"genre_scores_gemma":[0.4774169,0.00002704574,0.5224038,0.0000288656,0.0000701559,6.929203e-7,0.000002284648,0.000004485492,0.00004581638],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6148267,"threshold_uncertainty_score":0.3776836,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2204833299","doi":"10.1016/j.jspi.2015.12.007","title":"A note on the construction of blocked two-level designs with general minimum lower order confounding","year":2016,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Mathematics; Confounding; Order (exchange); Statistics; Combinatorics; Econometrics","retraction":null,"screen_n_in":null,"score":{"opus":0.2133840983652915,"gpt":0.4634463099791541,"spread":0.2500622116138627,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002000886,0.0001225741,0.0003150996,0.0001300899,0.0001007144,0.000105192,0.0002287538,0.00004227498,0.0002793818],"category_scores_gemma":[0.006216031,0.00005014086,0.00002962363,0.0002011527,0.0005762395,0.0002001278,0.00003439678,0.000180049,0.000005926204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002607278,"about_ca_system_score_gemma":0.0001411857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006286316,"about_ca_topic_score_gemma":5.135209e-7,"domain_scores_codex":[0.9978991,0.0003277336,0.000618352,0.0001689769,0.0008179175,0.0001679819],"domain_scores_gemma":[0.9888886,0.009848147,0.0005123246,0.0001391219,0.0004873078,0.0001245318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.005842263,0.0002718704,0.0383789,0.00001772971,0.0001878329,0.0003120375,0.002169645,0.0007848475,0.3903696,0.3847935,0.003064819,0.173807],"study_design_scores_gemma":[0.01804245,0.0314864,0.169936,0.005495253,0.0004473461,0.003598303,0.008391859,0.05611347,0.1826292,0.5176018,0.003910804,0.002347102],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.268509,0.00001967622,0.7302467,0.0002877279,0.0001608156,0.00004522892,0.00003220716,0.000002488214,0.0006961779],"genre_scores_gemma":[0.6562793,0.000003763587,0.3435229,0.00007645911,0.00003995009,7.266083e-7,1.491913e-7,0.000004090811,0.00007263424],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3877704,"threshold_uncertainty_score":0.7441618,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2083828390","doi":"10.1016/j.jspi.2005.02.018","title":"Constructing non-regular robust parameter designs","year":2005,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Fractional factorial design; Mathematics; Selection (genetic algorithm); Orthogonal array; Variance (accounting); Mathematical optimization; Design of experiments; Rank (graph theory); Optimal design; Noise (video); Word (group theory); Factorial experiment; Algorithm; Statistics; Computer science; Artificial intelligence; Combinatorics","retraction":null,"screen_n_in":null,"score":{"opus":0.2522636315418321,"gpt":0.4727185011069364,"spread":0.2204548695651043,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00281263,0.0001379346,0.0004128012,0.0001847422,0.0001097705,0.0003362803,0.0003077443,0.00007081952,0.0003098938],"category_scores_gemma":[0.009788826,0.00009482777,0.00005131029,0.0001899365,0.0002947229,0.0005217918,0.00007013725,0.0003505716,0.00002691679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004132735,"about_ca_system_score_gemma":0.00008345594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003746806,"about_ca_topic_score_gemma":3.315264e-7,"domain_scores_codex":[0.9975756,0.0002590289,0.0009050255,0.0002138902,0.0008088782,0.0002376201],"domain_scores_gemma":[0.991118,0.007734176,0.0004520664,0.0001416508,0.0002901582,0.0002640073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004356467,0.0001571246,0.09323312,0.00001765075,0.0000877866,0.0003653161,0.00214233,0.009385065,0.01271493,0.0331956,0.009601093,0.8386644],"study_design_scores_gemma":[0.004522611,0.004583656,0.1319336,0.001030858,0.0002175934,0.003928523,0.01619857,0.605402,0.02686591,0.1965248,0.007066031,0.001725849],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1124314,0.0002382555,0.8848039,0.0001626088,0.0001558905,0.00004077476,0.00001160404,0.000005910721,0.00214971],"genre_scores_gemma":[0.522921,0.000003376674,0.4768642,0.0000873797,0.00007184531,3.89462e-7,3.302041e-7,0.000003912608,0.0000474956],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8369385,"threshold_uncertainty_score":0.9985521,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2026650613","doi":"10.1016/j.jspi.2008.01.005","title":"Robust estimation of error scale in nonparametric regression models","year":2008,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":15,"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":"Universidad Nacional de Río Cuarto","keywords":"Mathematics; Estimator; Outlier; Asymptotic distribution; Statistics; Nonparametric statistics; Robust regression; Nonparametric regression; M-estimator; Invariant estimator; Trimmed estimator; Robustness (evolution); Robust statistics; Scale parameter; Regression analysis; Efficient estimator; Econometrics; Applied mathematics; Minimum-variance unbiased estimator","retraction":null,"screen_n_in":null,"score":{"opus":0.2812909765685763,"gpt":0.4557264070767004,"spread":0.1744354305081241,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004929007,0.000110622,0.000443377,0.0001997105,0.00004976569,0.000008621189,0.00008027263,0.00006972749,0.00001301044],"category_scores_gemma":[0.003890542,0.00008045854,0.00002601527,0.0001816816,0.0001516958,0.0002390222,0.00002753409,0.0003010268,3.388272e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002351835,"about_ca_system_score_gemma":0.00005993151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008136933,"about_ca_topic_score_gemma":6.35377e-7,"domain_scores_codex":[0.9986494,0.00009577153,0.0006884805,0.000116363,0.0002931392,0.0001568534],"domain_scores_gemma":[0.9962862,0.002985029,0.0003735536,0.00008137824,0.0001539262,0.0001199598],"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":[0.0009121238,0.0008496111,0.01133309,0.0008011044,0.00005232717,0.0004854367,0.004696539,0.3925537,0.0005915063,0.4594923,0.001237636,0.1269945],"study_design_scores_gemma":[0.0004149492,0.0002497281,0.004963025,0.0004843539,0.00001806767,0.00009315192,0.00008291437,0.4498341,0.00009318073,0.5436803,0.000002535974,0.00008376519],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1645292,0.0001366995,0.8348759,0.00001977451,0.00003812419,0.00004750149,0.00002214186,0.000004340437,0.000326338],"genre_scores_gemma":[0.5077206,0.00003756616,0.4922124,0.000006334511,0.000008086197,6.486308e-7,8.165454e-7,0.000004307027,0.00000924121],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3431914,"threshold_uncertainty_score":0.4657624,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2026351033","doi":"10.1016/j.jspi.2010.04.055","title":"Exact nonparametric confidence, prediction and tolerance intervals based on multi-sample Type-II right censored data","year":2010,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":15,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Quantile; Statistics; Nonparametric statistics; Confidence interval; Censoring (clinical trials); Order statistic; CDF-based nonparametric confidence interval; Inference; Prediction interval; Sample size determination; Hypergeometric distribution; Sample (material); Econometrics; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.1084961400859103,"gpt":0.4096862949216015,"spread":0.3011901548356912,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0004057238,0.0001138209,0.0002352809,0.0001003226,0.0001636508,0.00008077206,0.0001581689,0.00007065235,0.0002741523],"category_scores_gemma":[0.01277532,0.00008830203,0.00001295253,0.0001565474,0.0001754283,0.0001573014,0.00004633886,0.0004103633,0.000004124223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001094277,"about_ca_system_score_gemma":0.00005773671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007173011,"about_ca_topic_score_gemma":0.000001415756,"domain_scores_codex":[0.9989394,0.00004623081,0.0004592977,0.0001819979,0.0002398851,0.0001332232],"domain_scores_gemma":[0.9946992,0.004408671,0.0002437942,0.0002119386,0.0002512025,0.0001851545],"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":[0.0003593272,0.0007975177,0.01356473,0.0002100677,0.00005472808,0.00003870718,0.0002711656,0.0002765945,0.001057161,0.9513384,0.01724442,0.01478724],"study_design_scores_gemma":[0.001100478,0.0004530463,0.1409448,0.0002623223,0.00007770024,0.00004728228,0.00004232043,0.8100309,0.0001006219,0.04516554,0.001602205,0.0001727732],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03516745,0.00001895183,0.9624802,0.0001833859,0.0001305201,0.0000875713,0.001709528,0.00001834862,0.0002039725],"genre_scores_gemma":[0.7893413,0.000009239881,0.2104159,0.00008502174,0.00003775167,0.000001856911,0.0000903281,0.000005229268,0.00001333539],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9061728,"threshold_uncertainty_score":0.9955405,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}