{"meta":{"query_hash":"6d9568b0ff1b","filters":{"venue":"Annals of the Institute of Statistical Mathematics"},"cohort_total":79,"direct_labels_cover":0,"predictions_cover":79,"exported":79,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/6d9568b0ff1b","api":"https://metacan.xera.ac/api/v1/cohort?venue=Annals+of+the+Institute+of+Statistical+Mathematics"},"results":[{"id":"W1171051319","doi":"10.1007/s10463-015-0521-1","title":"Erratum to: Parameterizing mixture models with generalized moments","year":2015,"lang":"en","type":"erratum","venue":"Annals of the Institute of Statistical Mathematics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mathematics; Applied mathematics; Statistics; Generalized method of moments; Econometrics; Statistical physics; Physics; Estimator","score_opus":0.0921754455224483,"score_gpt":0.33773490636735914,"score_spread":0.24555946084491084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1171051319","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000056790737,0.00028259822,0.9703566,0.0014295197,0.004491235,0.0005792342,0.00034385113,0.000039712104,0.022420501],"genre_scores_gemma":[0.00056314905,0.000095587064,0.98723346,0.0007162142,0.00014210153,0.00003101148,0.000030532345,0.00004939135,0.011138578],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965862,0.00015633178,0.0009685723,0.0005390845,0.0012642456,0.00048554954],"domain_scores_gemma":[0.9962206,0.00015625519,0.00081814395,0.0017603297,0.00072724995,0.00031745146],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008457902,0.0005170712,0.0012924348,0.0001635728,0.000089910216,0.00010763713,0.0025012577,0.0003760296,0.000004627494],"category_scores_gemma":[0.00049171405,0.0003176579,0.00019444604,0.0005462528,0.00033770708,0.00034904515,0.00080064655,0.0006172091,0.00000484358],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018406363,0.000156058,1.2469616e-7,0.00064026174,0.00014839807,0.000014374255,0.0006074938,0.000433654,0.00005326412,0.47581732,0.5194971,0.0026135428],"study_design_scores_gemma":[0.00027279626,0.00026953119,0.0000024656176,0.0016258297,0.00011342409,0.000027451915,0.000008391662,0.050973974,0.00061810424,0.92514384,0.020490516,0.0004536628],"about_ca_topic_score_codex":0.000044755176,"about_ca_topic_score_gemma":0.000012675888,"teacher_disagreement_score":0.49900657,"about_ca_system_score_codex":0.000030075842,"about_ca_system_score_gemma":0.0006188098,"threshold_uncertainty_score":0.9999275},"labels":[],"label_agreement":null},{"id":"W1487961078","doi":"10.1023/a:1012474807133","title":"Simultaneous Estimation of Several Intraclass Correlation Coefficients","year":2001,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Economics of Agriculture and Food Markets","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Estimator; Mathematics; Extremum estimator; Statistics; Shrinkage estimator; Applied mathematics; M-estimator; Multivariate statistics; Monte Carlo method; Shrinkage; Minimax estimator; Minimum-variance unbiased estimator","score_opus":0.03626457354556138,"score_gpt":0.2612741350939767,"score_spread":0.22500956154841528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1487961078","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.408777,0.00018102347,0.5695655,0.0008237174,0.0005571119,0.00037548432,0.00060859736,0.000014257068,0.019097365],"genre_scores_gemma":[0.9703678,0.00008792467,0.029264692,0.00005056274,0.00001687169,0.0000023780608,0.00001971837,0.0000083492405,0.00018173852],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986684,0.0000092564505,0.0009731745,0.00013923319,0.000072135546,0.00013784623],"domain_scores_gemma":[0.998424,0.0002954503,0.0008552714,0.00026575854,0.00011637096,0.00004316709],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033997922,0.00011276963,0.00042535886,0.000072040355,0.000041536085,0.000010708213,0.0002613997,0.0000849559,0.00004926309],"category_scores_gemma":[0.0010595784,0.00009288042,0.00009909256,0.00016725356,0.0002142519,0.00015278165,0.00006444486,0.00008599666,0.000024374793],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003317618,0.00037147512,0.00038522994,0.0002080847,0.00006979286,0.0000014739435,0.000258663,0.122399144,0.000028708682,0.8740718,0.0006514998,0.0015209612],"study_design_scores_gemma":[0.00045996025,0.00019281848,0.0042202347,0.00019563342,0.00003507527,0.000015032369,0.000054426364,0.43062946,0.00065152586,0.5615217,0.0017963712,0.00022775741],"about_ca_topic_score_codex":0.000040459094,"about_ca_topic_score_gemma":0.000008423643,"teacher_disagreement_score":0.5615908,"about_ca_system_score_codex":0.000014715556,"about_ca_system_score_gemma":0.00001882177,"threshold_uncertainty_score":0.37875536},"labels":[],"label_agreement":null},{"id":"W1518621087","doi":"10.1023/a:1022451015903","title":"The Exact and Limiting Distributions for the Number of Successes in Success Runs Within a Sequence of Markov-Dependent Two-State Trials","year":2002,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Public Health Ontario; University of Toronto; Toronto Public Health; University of Manitoba","funders":"","keywords":"Mathematics; Markov chain; Bernoulli trial; Statistic; Limiting; Statistics; Sufficient statistic; Applied mathematics; Beta-binomial distribution; Binomial distribution; Bernoulli's principle; Bernoulli distribution; Negative binomial distribution; Combinatorics; Random variable; Poisson distribution","score_opus":0.5820460240127906,"score_gpt":0.5564590340817828,"score_spread":0.02558698993100783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1518621087","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20367092,0.00035480707,0.77743566,0.0036409716,0.0007943563,0.0034162465,0.009622441,0.00002687455,0.001037741],"genre_scores_gemma":[0.6266818,0.0003880067,0.37272567,0.000026124475,0.000034850706,0.00006880525,0.0000022212269,0.000023113953,0.00004939524],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99380136,0.000882319,0.0038920373,0.00027415628,0.0007726827,0.00037742895],"domain_scores_gemma":[0.84229934,0.15389942,0.0024295442,0.00073125237,0.0005590987,0.000081373655],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.012033276,0.0002773517,0.0015676705,0.000048844387,0.00019385599,0.00004278677,0.0009400587,0.000112003996,0.000060768543],"category_scores_gemma":[0.25941253,0.00014230491,0.000275667,0.00038427723,0.002380601,0.00012272254,0.00029994504,0.00030278086,9.0127656e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018319197,0.0005631295,0.00043886164,0.0019324081,0.00028505523,0.0000029445996,0.0005321261,0.0001032308,0.00053586153,0.98849946,0.00030307224,0.0066206423],"study_design_scores_gemma":[0.0009667623,0.00010620864,0.00034329048,0.0010008994,0.0003331705,0.000011315142,0.00023939888,0.007352672,0.012198974,0.9772462,0.0000441316,0.00015694431],"about_ca_topic_score_codex":0.00015004817,"about_ca_topic_score_gemma":0.00012780543,"teacher_disagreement_score":0.4230109,"about_ca_system_score_codex":0.000019728002,"about_ca_system_score_gemma":0.000100375146,"threshold_uncertainty_score":0.8771423},"labels":[],"label_agreement":null},{"id":"W1521692154","doi":"10.1023/a:1012431008950","title":"Generalized Calibration Approach for Estimating Variance in Survey Sampling","year":2001,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Estimator; Mathematics; Extremum estimator; Variance (accounting); Statistics; M-estimator; Empirical distribution function; Econometrics","score_opus":0.311805362925203,"score_gpt":0.446048395560018,"score_spread":0.13424303263481502,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1521692154","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01055265,0.000015193487,0.9875082,0.00013247371,0.0001848876,0.00062261574,0.00045215865,0.00001736844,0.00051448104],"genre_scores_gemma":[0.058610037,0.000010487487,0.94116086,0.00005687466,0.00004154073,0.000044081644,0.000026606205,0.000023999502,0.000025504249],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977555,0.00018968643,0.0011573983,0.00023922187,0.000355289,0.0003028894],"domain_scores_gemma":[0.9942069,0.004469688,0.0005349729,0.00043232582,0.00028421535,0.00007190551],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0020028972,0.00020258187,0.00068464683,0.000073441035,0.00008278637,0.00002774511,0.0004004815,0.00010729994,0.00002312027],"category_scores_gemma":[0.01855933,0.00014714696,0.00009727011,0.00037558086,0.00030929662,0.00013263905,0.000091896996,0.00014552289,4.3239035e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006467254,0.00040052625,0.00035672233,0.0010525285,0.000033817167,0.0000011774181,0.00021036027,0.0007484361,0.0002475398,0.992062,0.000303419,0.0045188],"study_design_scores_gemma":[0.0003047713,0.00004617769,0.00093715877,0.00023461689,0.00002808617,0.000005314799,0.000022115706,0.267481,0.0005133339,0.73028314,0.00001700141,0.00012731258],"about_ca_topic_score_codex":0.00014616115,"about_ca_topic_score_gemma":0.00004335449,"teacher_disagreement_score":0.26673254,"about_ca_system_score_codex":0.000015576983,"about_ca_system_score_gemma":0.00009489566,"threshold_uncertainty_score":0.98970777},"labels":[],"label_agreement":null},{"id":"W1537823803","doi":"10.1023/a:1022478119885","title":"On the Positive Definiteness of the Information Matrix Under the Binary and Poisson Mixed Models","year":2002,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Mathematics; Positive definiteness; Applied mathematics; Poisson distribution; Generalized linear model; Generalized linear mixed model; Property (philosophy); Statistics; Variance (accounting); Positive-definite matrix","score_opus":0.14000370682179544,"score_gpt":0.35972916702858476,"score_spread":0.21972546020678932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1537823803","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09624139,0.00007907203,0.8880209,0.008354128,0.00026332293,0.00092633814,0.0009646233,0.000016572807,0.0051336563],"genre_scores_gemma":[0.8474026,0.000066142245,0.15195933,0.00047627513,0.000013767058,0.000018699708,0.000002283445,0.000016080261,0.000044870343],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99784577,0.00027776117,0.00087494863,0.00012608747,0.00065058924,0.00022487078],"domain_scores_gemma":[0.9906998,0.0074981847,0.00069961546,0.0007179544,0.00033135296,0.000053093783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091139536,0.00022149216,0.00044840755,0.000047917125,0.00023661008,0.000037943835,0.00066268933,0.00009843747,0.00005663404],"category_scores_gemma":[0.004234743,0.000091381895,0.00013339403,0.00031345684,0.0012618258,0.00018883229,0.00026258652,0.00026559713,0.0000050270337],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026012634,0.00020340885,0.000005179205,0.00040718575,0.0000744148,5.3632584e-7,0.0009631847,0.00016531214,0.00007761458,0.9943598,0.0018742447,0.0018430952],"study_design_scores_gemma":[0.00017603618,0.00011281829,0.00069490797,0.0005422563,0.000121612145,0.000010540147,0.00042963942,0.028363956,0.0018962816,0.9675126,0.000028121274,0.000111228546],"about_ca_topic_score_codex":0.00003864655,"about_ca_topic_score_gemma":0.000005812226,"teacher_disagreement_score":0.75116116,"about_ca_system_score_codex":0.000012408893,"about_ca_system_score_gemma":0.00004156816,"threshold_uncertainty_score":0.50696886},"labels":[],"label_agreement":null},{"id":"W1579664569","doi":"10.1023/a:1022463111224","title":"Beta Approximation to the Distribution of Kolmogorov-Smirnov Statistic","year":2002,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Kolmogorov–Smirnov test; Mathematics; Statistic; Beta distribution; Goodness of fit; Anderson–Darling test; Test statistic; Statistics; Simple (philosophy); BETA (programming language); F-distribution; Distribution (mathematics); Applied mathematics; Statistical hypothesis testing; Probability distribution; Mathematical analysis; Computer science","score_opus":0.18488499937142475,"score_gpt":0.36081387621232186,"score_spread":0.1759288768408971,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1579664569","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016045915,0.000066255554,0.9793825,0.0019265342,0.00028825508,0.0004319179,0.00096342043,0.000011544241,0.0008836289],"genre_scores_gemma":[0.9259121,0.000014715167,0.07372437,0.00005712188,0.000024373554,0.000011901302,0.000009833419,0.000009163121,0.00023643539],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997035,0.00009867613,0.0012106522,0.00020058546,0.00125183,0.00020320578],"domain_scores_gemma":[0.9957205,0.0021813053,0.00054568116,0.0008318001,0.0006368828,0.00008381902],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0017813505,0.00015173921,0.00045784592,0.000070114336,0.000097827724,0.000031306456,0.0010154452,0.000052278123,0.00010568963],"category_scores_gemma":[0.013679106,0.000078319485,0.00011320447,0.0006799157,0.0005317492,0.00012745442,0.00017873848,0.00011462058,0.0000466753],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014229993,0.00030595597,0.000033837063,0.00022462371,0.00004296548,0.0000012121637,0.0006692088,0.020356055,0.00022709154,0.9417994,0.026579354,0.009746048],"study_design_scores_gemma":[0.0003354566,0.00031013828,0.004339841,0.00045027092,0.00013054707,0.000016612945,0.00028967718,0.22527695,0.0064695925,0.7551956,0.006889859,0.00029541916],"about_ca_topic_score_codex":0.000022345017,"about_ca_topic_score_gemma":0.000005043696,"teacher_disagreement_score":0.90986615,"about_ca_system_score_codex":0.000015770667,"about_ca_system_score_gemma":0.000041633546,"threshold_uncertainty_score":0.9946291},"labels":[],"label_agreement":null},{"id":"W1581498141","doi":"10.1023/a:1022427530788","title":"Estimation of the Size and Mean Value of a Stigmatized Characteristic of a Hidden Gang in a Finite Population: A Unified Approach","year":2002,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Mathematics; Statistics; Population; Econometrics; Demography; Sociology","score_opus":0.1366706589260064,"score_gpt":0.34971027216190037,"score_spread":0.21303961323589396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1581498141","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85131955,0.00004422861,0.14689825,0.00016695428,0.000056451427,0.0006899306,0.0002926278,0.00002112366,0.0005108625],"genre_scores_gemma":[0.724784,0.00001794453,0.27513662,0.000009881734,0.0000043052387,0.000010936671,0.0000055580817,0.000012610547,0.000018113864],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975774,0.0001741861,0.0014628075,0.00014211136,0.00050189416,0.00014154775],"domain_scores_gemma":[0.99498135,0.0027978658,0.0013966842,0.0005436939,0.0002431177,0.00003726473],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0011055627,0.00017624555,0.0007771895,0.000113773385,0.000041394986,0.000007659078,0.00034191782,0.00010340416,0.000020078902],"category_scores_gemma":[0.0108114425,0.000117899646,0.000113038055,0.00041821814,0.00049352646,0.00010668493,0.000122032165,0.00013046837,2.7089635e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010747804,0.0016268486,0.0012768384,0.012176671,0.00017593369,9.678732e-7,0.008590016,0.0019221681,0.0018994627,0.96717954,0.00017800761,0.0048660883],"study_design_scores_gemma":[0.000642168,0.00011422746,0.02021926,0.002669793,0.00016586424,0.000008914272,0.00020302655,0.2367143,0.010467241,0.72861594,0.00000200815,0.00017723057],"about_ca_topic_score_codex":0.00017274168,"about_ca_topic_score_gemma":0.000012003342,"teacher_disagreement_score":0.23856355,"about_ca_system_score_codex":0.00001191644,"about_ca_system_score_gemma":0.00003538175,"threshold_uncertainty_score":0.9975209},"labels":[],"label_agreement":null},{"id":"W1590341284","doi":"10.1023/a:1022463318629","title":"On a Multiparameter Version of Tukey's Linear Sensitivity Measure and its Properties","year":2002,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Measure (data warehouse); Fisher information; Applied mathematics; Sensitivity (control systems); Monotone polygon; Matrix (chemical analysis); Inverse; Estimator; Statistics; Combinatorics; Computer science","score_opus":0.28481315149255765,"score_gpt":0.3974755580721092,"score_spread":0.11266240657955157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1590341284","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31965092,0.00012541916,0.6773956,0.00041957048,0.00013280075,0.00057764957,0.00056706887,0.000021211568,0.0011098081],"genre_scores_gemma":[0.63138,0.000036391844,0.36844584,0.00004113882,0.000008884258,0.000003683047,6.621929e-7,0.000014278037,0.000069090536],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99830383,0.00014224471,0.0006531023,0.00019111589,0.00051019253,0.00019951529],"domain_scores_gemma":[0.99655706,0.0022326063,0.000385163,0.00036936256,0.0003677741,0.000088047556],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.000614196,0.00019851215,0.0006369987,0.000053694206,0.00006605823,0.0000053895938,0.000150908,0.00009404375,0.00002922015],"category_scores_gemma":[0.0115599595,0.00012434342,0.000099819554,0.00011488882,0.0005099559,0.0001012747,0.00012542552,0.00017290817,0.000004129234],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011680747,0.0008773806,0.0000044030453,0.0023418902,0.00010428644,0.0000074673862,0.00081512955,0.00034168613,0.009076565,0.98099416,0.0005731481,0.004747094],"study_design_scores_gemma":[0.0005491864,0.000373535,0.000040625357,0.0014996905,0.00014139083,0.000014384787,0.00007488312,0.14091086,0.07941742,0.77667934,0.00007495414,0.00022370086],"about_ca_topic_score_codex":0.000008365801,"about_ca_topic_score_gemma":0.0000034160598,"teacher_disagreement_score":0.3117291,"about_ca_system_score_codex":0.000007825572,"about_ca_system_score_gemma":0.000017370425,"threshold_uncertainty_score":0.9967661},"labels":[],"label_agreement":null},{"id":"W1978454503","doi":"10.1007/s10463-013-0425-x","title":"Estimation of a non-negative location parameter with unknown scale","year":2013,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Simons Foundation","keywords":"Mathematics; Minimax estimator; Estimator; Location parameter; Scale parameter; Minimax; Invariant estimator; Applied mathematics; Bayes' theorem; Univariate; Mathematical optimization; Statistics; Minimum-variance unbiased estimator; Bayesian probability","score_opus":0.08913341217558703,"score_gpt":0.3799429211026589,"score_spread":0.2908095089270719,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978454503","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21377203,0.0000057289235,0.783436,0.00022640392,0.00006201678,0.0005818432,0.00008723324,0.0000108193435,0.0018179158],"genre_scores_gemma":[0.48455724,0.0000031680615,0.51533395,0.000025372263,0.0000060848392,0.00002445692,0.0000018807526,0.000011071905,0.000036759448],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980536,0.00008150269,0.00094563805,0.00017573866,0.0005341365,0.00020937213],"domain_scores_gemma":[0.99456906,0.0031928753,0.0007712691,0.00053519226,0.00084581185,0.00008580611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044160773,0.00020221002,0.00062876125,0.00006736637,0.000051903964,0.00001664688,0.00033787749,0.00008525056,0.00010900987],"category_scores_gemma":[0.0076454696,0.000121031226,0.00007584882,0.00036214164,0.0010076441,0.00017495186,0.00009125112,0.00013942698,0.000010098823],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040112376,0.0006728884,0.00007912397,0.0024011193,0.00012065538,7.05688e-7,0.0010067322,0.0005438025,0.0008373542,0.96991795,0.00094507623,0.023434503],"study_design_scores_gemma":[0.00026710148,0.00028837193,0.0022506155,0.0009676114,0.0001048889,0.000004568373,0.000118704054,0.067912795,0.036494527,0.89144146,0.0000070877063,0.0001422851],"about_ca_topic_score_codex":0.00013744435,"about_ca_topic_score_gemma":0.000013431172,"teacher_disagreement_score":0.2707852,"about_ca_system_score_codex":0.000011372503,"about_ca_system_score_gemma":0.00010789601,"threshold_uncertainty_score":0.91528934},"labels":[],"label_agreement":null},{"id":"W1978806304","doi":"10.1007/s10463-007-0132-6","title":"Estimating a bounded parameter for symmetric distributions","year":2007,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Bounded function; Exponential family; Cauchy distribution; Scale parameter; Statistics; Exponential function; Natural exponential family; Exponential distribution; Applied mathematics; Combinatorics; Mathematical analysis","score_opus":0.16479561613828883,"score_gpt":0.4319752383352993,"score_spread":0.2671796221970105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978806304","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015323551,0.000011622307,0.97899425,0.0007135961,0.00021591234,0.0007555388,0.0026297846,0.00004371064,0.0013120326],"genre_scores_gemma":[0.43312854,0.0000011505117,0.5666413,0.00005250228,0.000026870664,0.0000360345,0.000057300596,0.000013037484,0.00004329367],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977576,0.000026665612,0.0012247047,0.00019850505,0.00044903398,0.00034350544],"domain_scores_gemma":[0.99254584,0.0055174665,0.00064161007,0.00051767984,0.0006395153,0.00013788807],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0010316145,0.00019254292,0.00046458872,0.00009703409,0.00022580191,0.00002531371,0.0003989815,0.00009892273,0.000048729627],"category_scores_gemma":[0.022858689,0.00014318626,0.00020247199,0.0006160864,0.00066867867,0.00009669691,0.00009038005,0.00013230937,0.000007003825],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017629603,0.00050991535,0.0000136754015,0.000587614,0.000058435602,5.323487e-7,0.000066626184,0.00002342908,0.00017421911,0.99220294,0.0034251965,0.0029197873],"study_design_scores_gemma":[0.0003123839,0.000063449195,0.0008111876,0.0001681862,0.0001268035,0.000007832068,0.000042132837,0.024161562,0.0053834026,0.9680442,0.00072704453,0.00015180245],"about_ca_topic_score_codex":0.000011660137,"about_ca_topic_score_gemma":0.000008027912,"teacher_disagreement_score":0.417805,"about_ca_system_score_codex":0.00003091115,"about_ca_system_score_gemma":0.000090721915,"threshold_uncertainty_score":0.9853722},"labels":[],"label_agreement":null},{"id":"W1979977159","doi":"10.1007/s10463-015-0520-2","title":"Testing the constancy of Spearman’s rho in multivariate time series","year":2015,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Mathematics; Resampling; Multivariate statistics; Rank correlation; Statistics; Series (stratigraphy); Null hypothesis; Null distribution; Null (SQL); Applied mathematics; Monte Carlo method; Rank (graph theory); Spearman's rank correlation coefficient; Statistical hypothesis testing; Test statistic; Combinatorics; Computer science; Data mining","score_opus":0.1924159092056419,"score_gpt":0.3097835461785308,"score_spread":0.11736763697288893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979977159","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9020756,0.0006777098,0.06916055,0.0012751608,0.00041276254,0.00056604075,0.0009808698,0.000016416761,0.024834884],"genre_scores_gemma":[0.93786293,0.000020249621,0.06198306,0.00003118846,0.000016056327,0.000003183014,0.0000020878122,0.000009414953,0.00007181472],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986118,0.000019468367,0.0010007444,0.00012267326,0.00008824918,0.00015707412],"domain_scores_gemma":[0.9985824,0.00031520825,0.0005754954,0.00032532585,0.00016352015,0.000038002778],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010739707,0.00010360114,0.0004692151,0.00006064863,0.00003619793,0.000009478473,0.0003118262,0.00005261679,0.000017010558],"category_scores_gemma":[0.0044081844,0.00007453742,0.000061765735,0.00024277558,0.00041477964,0.00014347659,0.0001169655,0.0001152796,0.000018726407],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002931386,0.000188096,0.0049334527,0.00023765792,0.00002544852,0.0000013672255,0.0015061637,0.001425668,0.00013317165,0.99065953,0.00027785898,0.0005822859],"study_design_scores_gemma":[0.00033645416,0.000084204024,0.0127364965,0.00030478288,0.000011077987,0.0000028494328,0.00014202103,0.060049,0.00081054395,0.9248628,0.0005330462,0.00012670034],"about_ca_topic_score_codex":0.0005925177,"about_ca_topic_score_gemma":0.000029618406,"teacher_disagreement_score":0.065796696,"about_ca_system_score_codex":0.000012834761,"about_ca_system_score_gemma":0.0000726303,"threshold_uncertainty_score":0.5277327},"labels":[],"label_agreement":null},{"id":"W1981088595","doi":"10.1007/s10463-006-0095-z","title":"Local mixtures of the exponential distribution","year":2007,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Universidad Nacional Autónoma de México; Consejo Nacional de Ciencia y Tecnología","keywords":"Mathematics; Class (philosophy); Exponential family; Affine transformation; Applied mathematics; Statistical inference; Inference; Exponential function; Simple (philosophy); Exponential distribution; Distribution (mathematics); Type (biology); Scale (ratio); Statistical model; Statistical physics; Statistics; Mathematical analysis; Pure mathematics; Computer science; Artificial intelligence","score_opus":0.04069839359092124,"score_gpt":0.32356410519885803,"score_spread":0.2828657116079368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981088595","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009455642,0.000052528263,0.98839533,0.0006590676,0.00041626632,0.00015708164,0.00010156902,0.000008961652,0.0007535556],"genre_scores_gemma":[0.6331611,0.0000061117616,0.36672083,0.00006800425,0.000015887717,9.206799e-7,0.000001512235,0.0000034569557,0.000022139013],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985647,0.000063407795,0.00058171543,0.0001317735,0.0004694885,0.00018886723],"domain_scores_gemma":[0.9984085,0.00031820362,0.00037070483,0.00064471544,0.00020309641,0.000054764518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093124044,0.00011243621,0.00027530896,0.000023880191,0.0000682036,0.000011639644,0.001017559,0.0000721415,0.0000047807043],"category_scores_gemma":[0.00054347864,0.00006155503,0.00014422931,0.00026124416,0.000667818,0.000112246016,0.00032894115,0.00012320568,9.0092345e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009162015,0.00015817923,0.000008025387,0.00015883466,0.000024185512,0.0000013894202,0.0002215197,0.00004049245,0.0021985685,0.9768364,0.0009917308,0.019351516],"study_design_scores_gemma":[0.00014524697,0.00005481479,0.0012539368,0.00020297477,0.000030080195,0.000011924017,0.00001402424,0.007243357,0.2274048,0.7630107,0.0005338384,0.00009430528],"about_ca_topic_score_codex":0.000029788695,"about_ca_topic_score_gemma":0.000007870576,"teacher_disagreement_score":0.6237055,"about_ca_system_score_codex":0.000007841937,"about_ca_system_score_gemma":0.000071513816,"threshold_uncertainty_score":0.25101414},"labels":[],"label_agreement":null},{"id":"W1981302666","doi":"10.1007/bf02506883","title":"Improving on the minimum risk equivariant estimator of a location parameter which is constrained to an interval or a half-interval","year":2005,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Mathematics; Estimator; Equivariant map; Minimax estimator; Interval (graph theory); Minimax; Applied mathematics; Location parameter; Statistics; Upper and lower bounds; Minimum-variance unbiased estimator; Combinatorics; Mathematical optimization; Mathematical analysis; Pure mathematics","score_opus":0.1746526275047541,"score_gpt":0.4154949266124361,"score_spread":0.24084229910768198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981302666","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17127287,0.000006280764,0.82416123,0.0024685788,0.00013812567,0.0006889842,0.0006081818,0.000021630873,0.00063412817],"genre_scores_gemma":[0.5067616,0.0000027736053,0.4928736,0.00026329726,0.000030093543,0.000019662924,0.0000016190361,0.000018833989,0.000028484032],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9969649,0.0002600512,0.0014748399,0.00030553972,0.0006510243,0.00034365966],"domain_scores_gemma":[0.9905914,0.006563685,0.0009326042,0.0009610599,0.0007763177,0.0001749232],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0016779763,0.0003057545,0.0008040211,0.00008867948,0.000111053036,0.0000420454,0.0007896522,0.00011832798,0.00028388502],"category_scores_gemma":[0.04269696,0.00016445629,0.00014131772,0.0003826158,0.0005819766,0.000129979,0.00023687088,0.00028658676,0.000014348641],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034671725,0.0009858148,0.000011665744,0.0009494629,0.00015322841,0.000002490266,0.0019390237,0.00011634163,0.0010422395,0.9717524,0.0013629379,0.021337664],"study_design_scores_gemma":[0.00054680574,0.0016631085,0.00026020265,0.0018254638,0.00030911202,0.000022104816,0.0006179102,0.22762342,0.028243173,0.738404,0.00013906624,0.00034565205],"about_ca_topic_score_codex":0.00011393968,"about_ca_topic_score_gemma":0.00009544993,"teacher_disagreement_score":0.33548874,"about_ca_system_score_codex":0.000024225923,"about_ca_system_score_gemma":0.00021773107,"threshold_uncertainty_score":0.9653668},"labels":[],"label_agreement":null},{"id":"W1988281501","doi":"10.1007/s10463-013-0424-y","title":"Some binary start-up demonstration tests and associated inferential methods","year":2013,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Binary number; Sequence (biology); Series (stratigraphy); Statistical hypothesis testing; Distribution (mathematics); Class (philosophy); Statistics; Applied mathematics; Computer science; Arithmetic; Artificial intelligence; Mathematical analysis","score_opus":0.16180048252054996,"score_gpt":0.43904643300914103,"score_spread":0.2772459504885911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988281501","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13367732,0.00003471353,0.86224276,0.0016564789,0.00018757404,0.00070545066,0.0007504942,0.000052815187,0.0006923732],"genre_scores_gemma":[0.6640468,0.000023241093,0.33561528,0.00009066509,0.000019383682,0.0000454364,0.00004757773,0.000014217514,0.00009740634],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982574,0.00012390359,0.00087765465,0.00017078216,0.00036127612,0.0002089897],"domain_scores_gemma":[0.9966931,0.0018505086,0.00050905516,0.0003511876,0.00047125085,0.00012491462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048054793,0.00017968629,0.00042078982,0.00005888385,0.0001371515,0.000038463393,0.00023252999,0.000109035405,0.00019249848],"category_scores_gemma":[0.007727083,0.00013202625,0.000079340236,0.0002347661,0.00068734126,0.0002569847,0.00012309162,0.00014978925,0.000015942987],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004071919,0.00037969011,0.000042123975,0.00027010456,0.000061814746,2.7452373e-7,0.00011887738,0.000009765128,0.002569211,0.9881299,0.005259542,0.0031546257],"study_design_scores_gemma":[0.0002603026,0.00006196689,0.009952614,0.00015122806,0.000095107665,0.0000034598986,0.00006986758,0.01590728,0.0039568194,0.9693178,0.00008384928,0.00013971585],"about_ca_topic_score_codex":0.000037342383,"about_ca_topic_score_gemma":0.000006922447,"teacher_disagreement_score":0.53036946,"about_ca_system_score_codex":0.000014984421,"about_ca_system_score_gemma":0.00008139371,"threshold_uncertainty_score":0.9250598},"labels":[],"label_agreement":null},{"id":"W1990608894","doi":"10.1007/s10463-006-0070-8","title":"Progressive censoring from heterogeneous distributions with applications to robustness","year":2006,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Censoring (clinical trials); Mathematics; Robustness (evolution); Order statistic; Exponential distribution; Exponential function; Probability density function; Applied mathematics; Statistics; Exponential family; Econometrics; Mathematical analysis","score_opus":0.08301678619024247,"score_gpt":0.3688059474598679,"score_spread":0.2857891612696254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990608894","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03572228,0.000017685326,0.9565237,0.00079814164,0.000037585243,0.0008805447,0.005034486,0.00005391893,0.00093161745],"genre_scores_gemma":[0.59993523,0.0000019110767,0.39954796,0.000029877294,0.000036950434,0.00022621157,0.00016393856,0.000017753977,0.000040172905],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99822867,0.000032366974,0.0007707885,0.00024212875,0.00047564015,0.00025042906],"domain_scores_gemma":[0.99741393,0.00095459126,0.00042810346,0.0006331979,0.0004414818,0.00012869184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013134534,0.00020397702,0.00039776653,0.00004799465,0.00019139778,0.000029164528,0.00041405114,0.000067116154,0.00010724382],"category_scores_gemma":[0.00083701237,0.0001428024,0.00008881342,0.00047173444,0.0005258278,0.00007328015,0.00010402494,0.00011321739,0.000015002309],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015230947,0.00065644627,0.000028332592,0.00017059836,0.000049279737,0.0000026155199,0.000038941642,0.001970223,0.00023174999,0.99483055,0.0012656081,0.0007404056],"study_design_scores_gemma":[0.00033264683,0.00007267803,0.0015294381,0.00032058754,0.00019040308,0.000020460142,0.000061393024,0.0052385265,0.018171158,0.9716511,0.0021176608,0.0002939594],"about_ca_topic_score_codex":0.00006968224,"about_ca_topic_score_gemma":0.000028103213,"teacher_disagreement_score":0.5642129,"about_ca_system_score_codex":0.00002642123,"about_ca_system_score_gemma":0.00007674163,"threshold_uncertainty_score":0.5823313},"labels":[],"label_agreement":null},{"id":"W1992572895","doi":"10.1023/a:1004152916478","title":"On the Bessel Distribution and Related Problems","year":2000,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":75,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bessel function; von Mises distribution; Mathematics; Bessel process; Computation; Distribution (mathematics); Applied mathematics; Bayesian probability; Monte Carlo method; Statistical physics; von Mises yield criterion; Algorithm; Statistics; Mathematical analysis; Physics","score_opus":0.04085020324197114,"score_gpt":0.296292397445917,"score_spread":0.25544219420394587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992572895","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018100195,0.000043869357,0.9727342,0.004199788,0.000079331825,0.00020038882,0.00006486277,0.000014006471,0.004563353],"genre_scores_gemma":[0.7313678,0.000103792365,0.26792482,0.00027834787,0.000008681435,0.0000076045835,0.0000034430816,0.000006587481,0.00029892588],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991085,0.00006848209,0.00032965912,0.00012885622,0.00023778938,0.00012669283],"domain_scores_gemma":[0.9988879,0.00042066397,0.00013101927,0.00044680623,0.00007192038,0.00004170544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005492905,0.000094736824,0.00018394901,0.000012529095,0.00009266809,0.000026317437,0.00048062828,0.000047975715,0.000018920322],"category_scores_gemma":[0.00035910573,0.000048270886,0.000046364563,0.0001732791,0.00032373003,0.00010482509,0.00008395187,0.000118423566,0.000004282524],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002118323,0.00008849957,9.450259e-7,0.00006826408,0.000017025388,7.7015767e-7,0.00024852628,0.000058710157,0.000054116892,0.9736897,0.0012665072,0.02450483],"study_design_scores_gemma":[0.00007541939,0.000061793995,0.00018129118,0.0001732117,0.000011887909,0.00001069209,0.0000027341482,0.02270794,0.0011335271,0.9749688,0.00061283476,0.00005989918],"about_ca_topic_score_codex":0.000009047549,"about_ca_topic_score_gemma":9.728448e-7,"teacher_disagreement_score":0.7132676,"about_ca_system_score_codex":0.000003482309,"about_ca_system_score_gemma":0.000027060014,"threshold_uncertainty_score":0.19684295},"labels":[],"label_agreement":null},{"id":"W1992649304","doi":"10.1023/a:1004141117010","title":"Positron Emission Tomography and Random Coefficients Regression","year":2000,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mathematics; Positron emission tomography; Tomography; Connection (principal bundle); Nonparametric statistics; Parametric statistics; Algorithm; Statistics; Nuclear medicine; Geometry; Radiology; Medicine","score_opus":0.036505029180341875,"score_gpt":0.3559175744532861,"score_spread":0.3194125452729442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992649304","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90366876,0.00019949261,0.081170894,0.008111018,0.000056661727,0.00078828866,0.00009952533,0.000052566473,0.005852763],"genre_scores_gemma":[0.8849493,0.000237155,0.11416446,0.00027957628,0.00001517021,0.0000082310535,0.000010516947,0.00000861798,0.00032696096],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991473,0.000015877366,0.0003420216,0.000104085855,0.0002866658,0.00010408079],"domain_scores_gemma":[0.9993014,0.000117590986,0.00010552421,0.00028281377,0.00008379106,0.00010888696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020036478,0.00008630976,0.00027688552,0.00003424714,0.000056843237,0.0000050204376,0.00011005418,0.000048460413,0.00009881412],"category_scores_gemma":[0.0002863878,0.000047785954,0.00006411412,0.00014064022,0.00045443795,0.000028210252,0.00004256426,0.00009879599,0.0000018335295],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015542498,0.00712109,0.0029278584,0.007094061,0.0004004488,0.000039066606,0.0015885197,0.000036906644,0.12696712,0.36443138,0.16687281,0.32096648],"study_design_scores_gemma":[0.008903832,0.0015268874,0.015162286,0.019037947,0.0012661513,0.0003790394,0.00016244568,0.045989864,0.4110969,0.41096458,0.08463741,0.0008726617],"about_ca_topic_score_codex":0.000012920798,"about_ca_topic_score_gemma":1.6436603e-7,"teacher_disagreement_score":0.3200938,"about_ca_system_score_codex":0.000002614959,"about_ca_system_score_gemma":0.000024857334,"threshold_uncertainty_score":0.19486547},"labels":[],"label_agreement":null},{"id":"W1992713587","doi":"10.1007/bf02530550","title":"A characterization of the multivariate normal distribution by using the hazard gradient","year":2004,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University","keywords":"Multivariate statistics; Multivariate stable distribution; Mathematics; Matrix t-distribution; Normal-Wishart distribution; Multivariate normal distribution; Multivariate analysis; Statistics; Multivariate t-distribution; Inverse-Wishart distribution; Multivariate analysis of variance; Hazard; Wishart distribution; Distribution (mathematics); Mathematical analysis","score_opus":0.09984669352884282,"score_gpt":0.36742453266147596,"score_spread":0.2675778391326331,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992713587","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2261607,0.000004995269,0.7668217,0.0016237007,0.00012247237,0.00048109287,0.004680444,0.000012454819,0.00009243332],"genre_scores_gemma":[0.9737142,0.0000074203826,0.025984695,0.000083580635,0.000016557444,0.000021312308,0.00013149634,0.000013482402,0.000027274351],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981323,0.00007457581,0.00092365936,0.00014054537,0.000531091,0.00019782559],"domain_scores_gemma":[0.9977007,0.00041725367,0.00086372124,0.0005610844,0.00039753463,0.00005971417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038405388,0.00016840419,0.00033005042,0.000019139605,0.00024003464,0.000018234225,0.0004964784,0.00007379255,0.000029451425],"category_scores_gemma":[0.0023602745,0.0000911439,0.00014735492,0.0003877406,0.000888561,0.00010502798,0.00014805318,0.000150128,0.0000027159308],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011691097,0.00049252325,0.000019639647,0.00025608274,0.000047252037,1.6692549e-7,0.00026123816,0.0002528097,0.023507448,0.97452855,0.000378303,0.00024428804],"study_design_scores_gemma":[0.000699541,0.000057232206,0.00642672,0.0006177069,0.00028798988,0.00001551677,0.00014348053,0.017799763,0.14479557,0.8283736,0.00055012986,0.00023276194],"about_ca_topic_score_codex":0.000058046895,"about_ca_topic_score_gemma":0.00000743725,"teacher_disagreement_score":0.74755347,"about_ca_system_score_codex":0.00004062957,"about_ca_system_score_gemma":0.000118469274,"threshold_uncertainty_score":0.371674},"labels":[],"label_agreement":null},{"id":"W1995722058","doi":"10.1007/bf02509240","title":"Testing for serial correlation of unknown form in cointegrated time series models","year":2005,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Mathematics; Statistics; Estimator; Test statistic; Autoregressive model; Series (stratigraphy); Applied mathematics; Autocorrelation; Nuisance parameter; Univariate; Truncation (statistics); Asymptotic distribution; Smoothing; Statistic; Multivariate statistics; Statistical hypothesis testing","score_opus":0.10206024534901126,"score_gpt":0.28761955270996703,"score_spread":0.18555930736095577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995722058","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4644951,0.00010427019,0.5300999,0.0003248349,0.00016022964,0.00044975718,0.0009642054,0.000009741584,0.00339193],"genre_scores_gemma":[0.79426974,0.000013174948,0.20556924,0.00001549864,0.000023166345,0.000006951056,0.00001251776,0.000009795174,0.00007990048],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985586,0.00000626822,0.0011073138,0.00012381058,0.000056389432,0.00014762649],"domain_scores_gemma":[0.9987626,0.00025502077,0.00057888945,0.00019142352,0.000187407,0.000024644665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057168945,0.000101815,0.000478725,0.000082218685,0.000038216967,0.0000075036896,0.00017286449,0.00007889398,0.000013040781],"category_scores_gemma":[0.0019156267,0.0000897498,0.00007798389,0.00019497455,0.00015926822,0.00030695344,0.000041866213,0.000074688505,0.00000418469],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060840182,0.00016908837,0.0003683249,0.00028896154,0.000015102442,1.102625e-7,0.0005531045,0.03188044,0.00016784582,0.96496755,0.00010409675,0.0014245196],"study_design_scores_gemma":[0.00019556424,0.000069998045,0.00045135565,0.000137196,0.000005476282,5.901387e-7,0.000013664349,0.49150404,0.00073084893,0.5067086,0.0001237341,0.000058943093],"about_ca_topic_score_codex":0.00015035267,"about_ca_topic_score_gemma":0.00007437187,"teacher_disagreement_score":0.4596236,"about_ca_system_score_codex":0.000017920143,"about_ca_system_score_gemma":0.000049768005,"threshold_uncertainty_score":0.3659891},"labels":[],"label_agreement":null},{"id":"W1999456916","doi":"10.1023/a:1004148814661","title":"Joint Distribution of Rises and Falls","year":2000,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Mathematics; Joint probability distribution; Markov chain; Applied mathematics; Joint (building); Distribution (mathematics); Marginal distribution; Parametric statistics; Statistical inference; Generating function; Statistics; Combinatorics; Random variable; Mathematical analysis","score_opus":0.05618700145579095,"score_gpt":0.312606646524457,"score_spread":0.2564196450686661,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999456916","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045191146,0.00007836971,0.9525996,0.0004785374,0.00005477478,0.00010429886,0.00012380266,0.0000075767143,0.0013619196],"genre_scores_gemma":[0.4430272,0.00009535235,0.5567741,0.00004497471,0.000006406405,0.0000013109284,0.0000015960048,0.0000026520859,0.000046434685],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99908525,0.000041990177,0.00042535298,0.00011218886,0.00022484308,0.000110406814],"domain_scores_gemma":[0.9991374,0.00015453412,0.00018278386,0.00036617383,0.00010995229,0.000049172733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036446165,0.0000855709,0.00028642424,0.00001856522,0.000034440844,0.000011832674,0.0003369515,0.000040784416,0.0000135932505],"category_scores_gemma":[0.000280701,0.000055766737,0.000057502155,0.00012772006,0.00034463266,0.00012972273,0.00010583305,0.000059655984,0.0000012558216],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037725024,0.00011547094,0.0000063086795,0.00022785904,0.000018160972,9.320671e-7,0.00023566668,0.000023665047,0.00044432702,0.9355634,0.00045899607,0.06290147],"study_design_scores_gemma":[0.00013527331,0.00009085567,0.0013790603,0.0002481528,0.000024072144,0.00001146853,0.0000065597687,0.012245309,0.021049578,0.96409136,0.0006276992,0.00009058854],"about_ca_topic_score_codex":0.000022103091,"about_ca_topic_score_gemma":0.0000012963837,"teacher_disagreement_score":0.39783606,"about_ca_system_score_codex":0.0000026473217,"about_ca_system_score_gemma":0.00003554917,"threshold_uncertainty_score":0.22741015},"labels":[],"label_agreement":null},{"id":"W2000683594","doi":"10.1007/s10463-014-0470-0","title":"Minimax design criterion for fractional factorial designs","year":2014,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Minimax; Mathematics; Optimal design; Fractional factorial design; Estimator; Factorial experiment; Optimality criterion; Minimax estimator; Mathematical optimization; Applied mathematics; Mean squared error; TRACE (psycholinguistics); Matrix (chemical analysis); Statistics; Minimum-variance unbiased estimator","score_opus":0.5060403338934417,"score_gpt":0.5212604005461885,"score_spread":0.015220066652746778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000683594","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033747915,0.000016266113,0.9930506,0.00038939647,0.0012022451,0.00047904867,0.00018743747,0.000011259721,0.0012889566],"genre_scores_gemma":[0.24485427,0.0000025566271,0.75474864,0.00011574185,0.00010323965,0.000018723824,0.00000257353,0.000012829319,0.00014141183],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99679846,0.00034113755,0.0011167775,0.00026855484,0.0012501519,0.00022493917],"domain_scores_gemma":[0.98792803,0.010133014,0.0006245501,0.00056297134,0.0006473363,0.00010411024],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004352587,0.00017377455,0.0005396308,0.0001030282,0.00012649196,0.00006642228,0.00085910095,0.00009932423,0.00014666918],"category_scores_gemma":[0.028347215,0.00010861109,0.00020364586,0.00025647003,0.0005524422,0.00027503606,0.00013175304,0.00009479989,0.000021881597],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035994442,0.0005220115,0.000025132345,0.00012749758,0.000062974075,7.066706e-7,0.00053320755,0.0015393251,0.05358408,0.90991914,0.020701682,0.012624304],"study_design_scores_gemma":[0.00032849726,0.00042563365,0.00019674053,0.00006731471,0.000029033807,0.0000044145368,0.00007570734,0.028249461,0.10552683,0.8597339,0.00522525,0.00013725218],"about_ca_topic_score_codex":0.000011076339,"about_ca_topic_score_gemma":9.1813234e-7,"teacher_disagreement_score":0.24147947,"about_ca_system_score_codex":0.000013885069,"about_ca_system_score_gemma":0.000106643885,"threshold_uncertainty_score":0.9798374},"labels":[],"label_agreement":null},{"id":"W2001455389","doi":"10.1007/bf02915433","title":"Derivation of mixture distributions and weighted likelihood function as minimizers of KL-divergence subject to constraints","year":2005,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Kullback–Leibler divergence; Divergence (linguistics); Applied mathematics; Mixture model; Entropy (arrow of time); Likelihood function; Statistics; Maximum likelihood","score_opus":0.08397289070544389,"score_gpt":0.3907210040042528,"score_spread":0.3067481132988089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001455389","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15125373,0.000033407498,0.8461116,0.00042066487,0.00008790615,0.0003678162,0.0012525817,0.000009955508,0.00046237189],"genre_scores_gemma":[0.47556853,0.000032963082,0.524318,0.000033311193,0.000010666251,0.000005934415,0.00000834017,0.000008091489,0.000014195909],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981375,0.00007479453,0.0009861735,0.00018516147,0.00041257375,0.00020381073],"domain_scores_gemma":[0.9969476,0.0014487567,0.0005928776,0.00034471016,0.00054350455,0.00012254114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000486561,0.00017976925,0.00058606087,0.00007093703,0.00006271933,0.000005254806,0.00021013095,0.000098061704,0.000067103545],"category_scores_gemma":[0.005758149,0.00013291543,0.00009398498,0.0002611253,0.00081273075,0.000115898176,0.000110846995,0.00011479108,0.0000016367286],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010094548,0.0004197525,0.00004227016,0.0007789087,0.00010130487,7.301834e-7,0.0004843883,0.000057385165,0.008539468,0.9733505,0.0005315427,0.015592763],"study_design_scores_gemma":[0.0003354112,0.00025640562,0.00064864877,0.0004797401,0.00015440321,0.0000066832436,0.00015832603,0.001799029,0.057883684,0.93795,0.00018679346,0.0001408499],"about_ca_topic_score_codex":0.00001764334,"about_ca_topic_score_gemma":0.000012273724,"teacher_disagreement_score":0.3243148,"about_ca_system_score_codex":0.000012726564,"about_ca_system_score_gemma":0.000087966466,"threshold_uncertainty_score":0.6893458},"labels":[],"label_agreement":null},{"id":"W2003114898","doi":"10.1007/bf02530502","title":"Exact likelihood inference based on Type-I and Type-II hybrid censored samples from the exponential distribution","year":2003,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":349,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Bhattacharyya distance; Censoring (clinical trials); Exponential distribution; Statistics; Upper and lower bounds; Estimator; Applied mathematics; Sample size determination; Coverage probability; Order statistic; Confidence interval; Mathematical analysis; Computer science","score_opus":0.1070624961929821,"score_gpt":0.368312949380911,"score_spread":0.26125045318792894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003114898","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08813009,0.000024289548,0.903657,0.001378602,0.00017807403,0.000421708,0.0053485935,0.000030610172,0.0008310083],"genre_scores_gemma":[0.9388346,0.000018861825,0.06062598,0.00019396801,0.00001851361,0.000013254592,0.00026418292,0.000013182688,0.000017419323],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99843156,0.000110224835,0.0006140629,0.00019857314,0.00043912133,0.00020646314],"domain_scores_gemma":[0.9955889,0.0029696762,0.0003426117,0.00054578227,0.00045389048,0.00009911424],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0003622643,0.0001890462,0.00033333368,0.000020722706,0.00026840903,0.000029960274,0.00027474115,0.00006272422,0.00024143334],"category_scores_gemma":[0.015180308,0.0001181598,0.00006273231,0.00027539718,0.0006009606,0.00006165288,0.00007228839,0.00015797067,0.000012820561],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030489464,0.00042953042,0.000059762744,0.00009680954,0.000034764384,6.945117e-7,0.000073114476,0.000051062387,0.0003067676,0.99128026,0.0069635166,0.00067324715],"study_design_scores_gemma":[0.0004203786,0.00014864061,0.004508725,0.000255548,0.00014001419,0.0000032515018,0.00007098393,0.013467029,0.0088348305,0.969549,0.0024092712,0.00019231427],"about_ca_topic_score_codex":0.000034709992,"about_ca_topic_score_gemma":0.0000059958006,"teacher_disagreement_score":0.85070455,"about_ca_system_score_codex":0.000016515582,"about_ca_system_score_gemma":0.0001329397,"threshold_uncertainty_score":0.99311525},"labels":[],"label_agreement":null},{"id":"W2004659988","doi":"10.1007/s10463-012-0381-x","title":"Recursive equations in finite Markov chain imbedding","year":2012,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Markov chain; Mathematics; Independent and identically distributed random variables; Applied mathematics; Continuous-time Markov chain; Markov process; Discrete phase-type distribution; Finite state; Markov property; Additive Markov chain; Markov chain mixing time; Markov model; Discrete mathematics; Random variable; Statistics","score_opus":0.2496363425207121,"score_gpt":0.46783583616790597,"score_spread":0.21819949364719388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004659988","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014425312,0.00009189844,0.97947854,0.0007786636,0.0005965643,0.00024904657,0.00024827925,0.000010228516,0.0041214977],"genre_scores_gemma":[0.72359085,0.000011938801,0.2761726,0.000048637114,0.00004756383,0.000009395902,0.000002197216,0.000010431768,0.00010635409],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99674016,0.00012365614,0.0013160127,0.00020347552,0.0012263947,0.00039032561],"domain_scores_gemma":[0.9882539,0.0099235065,0.0006328362,0.0005582551,0.00048688534,0.00014464493],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0024615065,0.00016172216,0.00049426605,0.00018551278,0.00009515898,0.0000299531,0.00076587603,0.00007242657,0.00009246494],"category_scores_gemma":[0.07606857,0.00010828873,0.00009048768,0.00082133396,0.00061408075,0.00054185645,0.00026600735,0.00021275014,0.00004261351],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002145447,0.000311913,0.0007363291,0.0001303794,0.000017807128,0.0000026126793,0.001420545,0.0015479297,0.00025821882,0.9842512,0.00056579313,0.010735828],"study_design_scores_gemma":[0.00017336888,0.000039814793,0.0023886827,0.0002923711,0.000017876304,0.0000024743088,0.00066892104,0.0103674745,0.0026679342,0.982704,0.00052605965,0.00015105445],"about_ca_topic_score_codex":0.000018825838,"about_ca_topic_score_gemma":0.000012446716,"teacher_disagreement_score":0.7091656,"about_ca_system_score_codex":0.000025079686,"about_ca_system_score_gemma":0.000072253766,"threshold_uncertainty_score":0.9317141},"labels":[],"label_agreement":null},{"id":"W2014468891","doi":"10.1007/s10463-009-0222-8","title":"Forms of four-word indicator functions with implications to two-level factorial designs","year":2009,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; DePaul University","keywords":"Fractional factorial design; Mathematics; Factorial; Factorial experiment; Statistics; Plackett–Burman design; Factorial analysis; Econometrics; Arithmetic; Mathematical analysis","score_opus":0.4405702350079293,"score_gpt":0.49258100385881126,"score_spread":0.05201076885088196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014468891","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0756098,0.0000099872095,0.9186185,0.0010518521,0.00020133189,0.00052317034,0.0006249723,0.00001231046,0.0033480763],"genre_scores_gemma":[0.5454178,0.0000013802137,0.45436105,0.00010709301,0.000020962416,0.000009284884,0.0000021852481,0.0000069164034,0.00007332847],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99703395,0.00010030155,0.0011597965,0.00026487623,0.0012031341,0.0002379676],"domain_scores_gemma":[0.99599504,0.0016506987,0.0006970773,0.00090787606,0.0005636464,0.00018564945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014079531,0.00018242547,0.00057318417,0.00019971989,0.000117256706,0.000038311282,0.0010246994,0.00006550963,0.00009776635],"category_scores_gemma":[0.0047468566,0.000102687336,0.00013638588,0.0008558462,0.0004981922,0.00024645423,0.00013058993,0.000119572214,0.000027603084],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024022395,0.00094088895,0.00029087462,0.000046937697,0.00009667524,0.0000016018423,0.0010689904,0.0014787763,0.043768656,0.92259,0.0046954555,0.02478088],"study_design_scores_gemma":[0.00055166695,0.001100582,0.016716212,0.00015114319,0.00007875265,0.000015856438,0.00038089725,0.00048757618,0.081214525,0.898277,0.0007744278,0.00025138562],"about_ca_topic_score_codex":0.000019975747,"about_ca_topic_score_gemma":0.000011256852,"teacher_disagreement_score":0.46980798,"about_ca_system_score_codex":0.000018618475,"about_ca_system_score_gemma":0.00019481945,"threshold_uncertainty_score":0.56827736},"labels":[],"label_agreement":null},{"id":"W2015828990","doi":"10.1023/a:1017564907869","title":"Boundary Bias Correction for Nonparametric Deconvolution","year":2000,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Deconvolution; Mathematics; Estimator; Nonparametric statistics; Kernel density estimation; Kernel (algebra); Boundary (topology); Mean squared error; Density estimation; Random variable; Applied mathematics; Statistics; Convergence (economics); Variable (mathematics); Rate of convergence; Mathematical analysis; Combinatorics; Computer science","score_opus":0.21376384285232522,"score_gpt":0.4180290124447216,"score_spread":0.2042651695923964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015828990","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08543279,0.000052409163,0.9058593,0.00026728248,0.00074142637,0.0006476856,0.00044960962,0.000033308723,0.00651618],"genre_scores_gemma":[0.19284862,0.000055673783,0.80603427,0.00010576345,0.000055673718,0.000034852284,0.000007910177,0.000025209176,0.000832003],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99810666,0.00008481952,0.00094713963,0.00019584839,0.00039856715,0.0002669492],"domain_scores_gemma":[0.9940865,0.004598915,0.00040953173,0.0004552748,0.000361232,0.00008851413],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00092138204,0.00018836661,0.0005486281,0.00008661808,0.00013476294,0.000023314597,0.00033712242,0.00011016003,0.00036405356],"category_scores_gemma":[0.014309468,0.00013219722,0.0001768462,0.00038848733,0.0005919111,0.00009974739,0.000046421246,0.00014162334,0.000013255423],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000718486,0.00048001448,0.00003798771,0.00077174476,0.000067554814,6.839648e-7,0.00015007108,0.00005412448,0.00015218214,0.9066214,0.01053879,0.081053615],"study_design_scores_gemma":[0.0002773805,0.00024413392,0.00078446436,0.00029574244,0.00010910888,0.000010969694,0.00003190449,0.01703575,0.004284811,0.97380877,0.0029595494,0.00015739244],"about_ca_topic_score_codex":0.00003747115,"about_ca_topic_score_gemma":0.000008496464,"teacher_disagreement_score":0.10741583,"about_ca_system_score_codex":0.000019264826,"about_ca_system_score_gemma":0.00011390617,"threshold_uncertainty_score":0.9939934},"labels":[],"label_agreement":null},{"id":"W2021930287","doi":"10.1007/s10463-006-0035-y","title":"Confidence Intervals for Quantiles and Tolerance Intervals Based on Ordered Ranked Set Samples","year":2006,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University; McMaster University","funders":"","keywords":"Confidence interval; Quantile; Mathematics; CDF-based nonparametric confidence interval; Robust confidence intervals; Statistics; Tolerance interval; Coverage probability; RSS; Confidence and prediction bands; Order statistic; Confidence distribution; Confidence region; Inference; Computer science","score_opus":0.18303277303329363,"score_gpt":0.412504552691525,"score_spread":0.22947177965823135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021930287","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019260537,0.000019749199,0.9731384,0.0019027122,0.00007913406,0.0007276199,0.004207983,0.000033006196,0.0006308411],"genre_scores_gemma":[0.76650506,0.0000051748075,0.23306881,0.00021650721,0.000017123004,0.0000671915,0.00006365136,0.000015160955,0.00004131956],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982133,0.00005517184,0.0009646693,0.00021711721,0.00034547687,0.00020424639],"domain_scores_gemma":[0.994853,0.003723511,0.0005030286,0.00043126682,0.00042176875,0.00006739396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004675878,0.00020121066,0.00052924675,0.000055484237,0.00011809285,0.00003254119,0.00030762228,0.00007392344,0.00006642263],"category_scores_gemma":[0.004973873,0.00014706385,0.00012269536,0.00016187846,0.00069992355,0.00007229523,0.000055085395,0.00008959345,0.0000039179904],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052264593,0.00036803147,0.000018188497,0.0010222045,0.000028127824,3.963843e-7,0.000067391185,0.00024173169,0.00038315664,0.98997855,0.0074537946,0.0003861719],"study_design_scores_gemma":[0.0005322873,0.00010716675,0.0012075529,0.0006511288,0.00007324631,0.000002629044,0.000047307607,0.0663045,0.0070233634,0.92338145,0.000515615,0.00015376756],"about_ca_topic_score_codex":0.000043735767,"about_ca_topic_score_gemma":0.000024411078,"teacher_disagreement_score":0.74724454,"about_ca_system_score_codex":0.00001095382,"about_ca_system_score_gemma":0.000058717094,"threshold_uncertainty_score":0.599709},"labels":[],"label_agreement":null},{"id":"W2026903646","doi":"10.1007/bf02530552","title":"Fisher information ink-records","year":2004,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Estimator; Statistics; Fisher information; Exponential distribution; Upper and lower bounds; Sample size determination; Sample (material); Mathematical analysis","score_opus":0.10828971566031394,"score_gpt":0.38135766443832586,"score_spread":0.27306794877801194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026903646","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026712218,0.000005294754,0.9607009,0.0023987615,0.00017309622,0.00039276658,0.0010194806,0.000044507226,0.008552924],"genre_scores_gemma":[0.72334146,0.000009278717,0.27620608,0.0002766682,0.000018619998,0.000026927031,0.000050941235,0.000011164753,0.000058823007],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982357,0.000024058316,0.00096017803,0.00010313695,0.000487875,0.00018906068],"domain_scores_gemma":[0.99800193,0.0004818941,0.0005096633,0.00046642518,0.0004452618,0.000094831455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003078021,0.00015650006,0.00033841585,0.00006144097,0.000103752966,0.000023195804,0.00037078734,0.000084381296,0.0001664423],"category_scores_gemma":[0.0044536833,0.00011293802,0.00011179566,0.00033457056,0.000500467,0.00030991927,0.00009617622,0.00013405968,0.000055298413],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000076959195,0.00030399032,0.00000985427,0.00037930012,0.000031603144,3.5357652e-7,0.00022102271,0.00014805059,0.000057962163,0.99162525,0.0056599416,0.0015549809],"study_design_scores_gemma":[0.00035634596,0.00004473856,0.001436747,0.00018900118,0.000051106912,0.0000068079444,0.000081153754,0.0009378034,0.0032313948,0.9910292,0.0025086217,0.00012706175],"about_ca_topic_score_codex":0.00004070441,"about_ca_topic_score_gemma":0.000008975929,"teacher_disagreement_score":0.6966293,"about_ca_system_score_codex":0.00002560291,"about_ca_system_score_gemma":0.00012813888,"threshold_uncertainty_score":0.5331797},"labels":[],"label_agreement":null},{"id":"W2028479624","doi":"10.1007/s10463-014-0486-5","title":"The complex multinormal distribution, quadratic forms in complex random vectors and an omnibus goodness-of-fit test for the complex normal distribution","year":2014,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Goodness of fit; Anderson–Darling test; Mathematics; Omnibus test; Kolmogorov–Smirnov test; Asymptotic distribution; Empirical distribution function; Normality; Normal distribution; Distribution (mathematics); Quadratic equation; Applied mathematics; Statistical hypothesis testing; Statistics; Mathematical analysis","score_opus":0.09581776700980571,"score_gpt":0.35982630148065636,"score_spread":0.26400853447085065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028479624","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03451281,0.000021040922,0.9615335,0.0020503413,0.00007008244,0.0008261032,0.00086580095,0.000033338136,0.00008698379],"genre_scores_gemma":[0.9451211,0.000022687178,0.054502714,0.00011017354,0.000020603,0.000042940457,0.00016581947,0.000008763098,0.0000051785564],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99793345,0.00014884285,0.0009946604,0.00019958502,0.00043119106,0.0002922504],"domain_scores_gemma":[0.9947601,0.0034466353,0.0006200906,0.000687637,0.00040969535,0.000075866825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017842656,0.00020082633,0.00046270387,0.00003291425,0.00038064498,0.00010474424,0.0011092983,0.00007070589,0.0000036714343],"category_scores_gemma":[0.0024702942,0.00010931023,0.000100666206,0.00029547725,0.0010550426,0.00036286868,0.0002689536,0.00015065771,7.245969e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005747214,0.00036363155,0.00042095326,0.00023295637,0.000030414893,2.4168517e-7,0.00061627914,0.00067653967,0.0004957348,0.99197966,0.0013546639,0.0037714427],"study_design_scores_gemma":[0.0012461183,0.00037983706,0.050361607,0.00010662761,0.000043222048,0.000010715959,0.00015750117,0.80664253,0.002650898,0.1352825,0.0029040591,0.00021440463],"about_ca_topic_score_codex":0.000109609944,"about_ca_topic_score_gemma":0.00018041376,"teacher_disagreement_score":0.9106083,"about_ca_system_score_codex":0.000017838587,"about_ca_system_score_gemma":0.00007125179,"threshold_uncertainty_score":0.4457542},"labels":[],"label_agreement":null},{"id":"W2033944127","doi":"10.1023/a:1004101402897","title":"Start-Up Demonstration Tests with Rejection of Units upon Observing d Failures","year":2000,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Test (biology); Statistics; Function (biology); Statistical hypothesis testing; Distribution (mathematics); Calculus (dental); Applied mathematics; Mathematical analysis; Medicine","score_opus":0.0802316870046062,"score_gpt":0.3248804992497101,"score_spread":0.24464881224510387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033944127","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43600342,0.00004045276,0.56218517,0.0008606757,0.00004893303,0.00019621127,0.00003599914,0.000025207417,0.00060391397],"genre_scores_gemma":[0.86338276,0.000051114435,0.1364639,0.0000195312,0.000008146267,0.000003234399,0.000003123375,0.0000045756988,0.000063605454],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985033,0.000076022196,0.00049504405,0.00015919631,0.0006092179,0.00015720172],"domain_scores_gemma":[0.99811053,0.0005212724,0.00021940198,0.0005481826,0.00054563856,0.000054995064],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049757597,0.00010286549,0.0002833352,0.0000690681,0.00007977197,0.000028827319,0.000601722,0.000050121518,0.00003269575],"category_scores_gemma":[0.0010359322,0.000066811015,0.000054678854,0.00078632106,0.00031074486,0.00031854265,0.00008694849,0.000112462774,0.0000032503135],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010418825,0.00093458954,0.0014421251,0.0020353503,0.00027355278,0.000007921571,0.002105382,0.017071214,0.0037302524,0.84529626,0.00060287095,0.12639628],"study_design_scores_gemma":[0.0010158722,0.0014223154,0.017319765,0.0026677107,0.00019900406,0.000050491202,0.00042039505,0.3254997,0.113669254,0.53553474,0.0015755754,0.0006251725],"about_ca_topic_score_codex":0.00018409158,"about_ca_topic_score_gemma":0.00011446866,"teacher_disagreement_score":0.42737937,"about_ca_system_score_codex":0.000008816094,"about_ca_system_score_gemma":0.00017317443,"threshold_uncertainty_score":0.2724474},"labels":[],"label_agreement":null},{"id":"W2034173718","doi":"10.1007/s10463-005-0020-x","title":"Connections Between the Resolutions of General Two-level Factorial Designs","year":2006,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Prince Edward Island; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fractional factorial design; Mathematics; Factorial experiment; Factorial; Connection (principal bundle); Plackett–Burman design; Statistics; Mathematical analysis; Geometry","score_opus":0.4751025642495491,"score_gpt":0.5019135975057859,"score_spread":0.026811033256236794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034173718","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.070847385,0.00004837274,0.9184134,0.000733964,0.00066944095,0.00037669012,0.0012513013,0.000011352109,0.00764809],"genre_scores_gemma":[0.6035205,0.0000025648917,0.39599827,0.000024585841,0.00012537645,0.000006566486,0.0000040866425,0.00000884675,0.0003091704],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9964613,0.00036205968,0.0014398596,0.000209216,0.0012996669,0.00022793998],"domain_scores_gemma":[0.99267036,0.0051414976,0.00074947416,0.00079147855,0.0005819233,0.00006526936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025293336,0.00016226286,0.00054568023,0.00010733644,0.00020885517,0.000040903218,0.0011033692,0.00007498014,0.00010339042],"category_scores_gemma":[0.006952905,0.000087329674,0.0002219069,0.0006239095,0.0014410182,0.00016778026,0.00023966891,0.00015042357,0.000013316509],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002299097,0.00025144473,0.0003110913,0.000024020013,0.000055047392,7.1248644e-7,0.00022388088,0.0022441042,0.017242117,0.97058207,0.008160217,0.0008823272],"study_design_scores_gemma":[0.0003035661,0.0001375385,0.0063984096,0.00005760806,0.000074590214,0.000004811852,0.00014882348,0.0028392468,0.09340784,0.8952117,0.001285917,0.00012993868],"about_ca_topic_score_codex":0.00057808263,"about_ca_topic_score_gemma":0.000038397204,"teacher_disagreement_score":0.5326731,"about_ca_system_score_codex":0.000016141561,"about_ca_system_score_gemma":0.00014446407,"threshold_uncertainty_score":0.8323779},"labels":[],"label_agreement":null},{"id":"W2036776573","doi":"10.1007/s10463-006-0109-x","title":"The admissible parameter space for exponential smoothing models","year":2007,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":83,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Exponential smoothing; Smoothing; Mathematics; Observable; Applied mathematics; Exponential function; Parameter space; State space; Space (punctuation); Exponential family; Statistical physics; Econometrics; Mathematical analysis; Statistics; Computer science; Physics","score_opus":0.3438497451991275,"score_gpt":0.4666185973607811,"score_spread":0.12276885216165362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036776573","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017434508,0.000032512136,0.97634643,0.0024817477,0.00016169605,0.0004183488,0.000109516215,0.000017765009,0.0029974533],"genre_scores_gemma":[0.54255676,0.000008900373,0.45689553,0.000084026,0.00002783659,0.00001620134,0.0000012884376,0.000009069086,0.00040037144],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979052,0.000024199202,0.000912189,0.00017047364,0.0007508554,0.00023711644],"domain_scores_gemma":[0.9926938,0.0054836376,0.0005396188,0.0007239872,0.00048006212,0.000078927],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0035313154,0.00010616069,0.0002568449,0.000052152365,0.00027742234,0.00007411058,0.0010171041,0.000059149952,0.000011873516],"category_scores_gemma":[0.009088268,0.000053342694,0.0001596125,0.000284408,0.0005509883,0.00013580923,0.00018987666,0.000095976204,0.000003720606],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027661285,0.00008504924,0.0000045990205,0.000032530283,0.000014657894,2.8295975e-7,0.00018924009,0.00047224032,0.0003481464,0.97590977,0.011818491,0.011097311],"study_design_scores_gemma":[0.000073831914,0.00004785622,0.000029472645,0.0000645924,0.00001582744,0.0000023854354,0.000112243135,0.044419274,0.012066004,0.932774,0.010330577,0.000063957224],"about_ca_topic_score_codex":0.000024175915,"about_ca_topic_score_gemma":0.0000231786,"teacher_disagreement_score":0.5251223,"about_ca_system_score_codex":0.0000061434757,"about_ca_system_score_gemma":0.00006162901,"threshold_uncertainty_score":0.9992586},"labels":[],"label_agreement":null},{"id":"W2038552307","doi":"10.1007/s10463-007-0141-5","title":"Exact two-sample nonparametric test for quantile difference between two populations based on ranked set samples","year":2007,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Quantile; Statistics; Mathematics; Ranking (information retrieval); Nonparametric statistics; Estimator; Confidence interval; Null hypothesis; Sample size determination; Coverage probability; Statistical hypothesis testing; Inference; Nominal level; Sample (material); Econometrics; Population; Computer science; Artificial intelligence","score_opus":0.3085492212357678,"score_gpt":0.4657795066080027,"score_spread":0.15723028537223493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038552307","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025889792,0.0000044201906,0.95741916,0.0006095968,0.00009670408,0.0009339559,0.014474108,0.000051977568,0.0005202877],"genre_scores_gemma":[0.6018364,9.806796e-7,0.39771727,0.000084787986,0.000029347479,0.00003499826,0.00026073193,0.000017991839,0.000017502565],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9974266,0.00004622709,0.0012793966,0.00026510973,0.00061771204,0.00036493817],"domain_scores_gemma":[0.97562367,0.022348866,0.00066379696,0.0006795326,0.0005137762,0.00017038226],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00093417807,0.00026183607,0.000622262,0.00017229357,0.00024440556,0.000031350093,0.0004678254,0.00008610248,0.00009132768],"category_scores_gemma":[0.028951487,0.00019755663,0.0001944963,0.00065952557,0.0005029452,0.000066395754,0.00006217455,0.00016544743,0.000010190875],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028779772,0.00074108056,0.0009537837,0.00042608922,0.000038696,3.9042064e-7,0.000055697215,0.0003506578,0.00016347737,0.99395555,0.0010900447,0.002195735],"study_design_scores_gemma":[0.00092977664,0.00016631582,0.02014513,0.000258979,0.0001894256,0.0000012691834,0.000044163222,0.054243572,0.003855014,0.91968685,0.00023504702,0.0002444249],"about_ca_topic_score_codex":0.00008802826,"about_ca_topic_score_gemma":0.000049509697,"teacher_disagreement_score":0.57594657,"about_ca_system_score_codex":0.000033347424,"about_ca_system_score_gemma":0.00009989906,"threshold_uncertainty_score":0.9792281},"labels":[],"label_agreement":null},{"id":"W2043630120","doi":"10.1007/s10463-006-0083-3","title":"Saddlepoint approximations for multivariate M-estimates with applications to bootstrap accuracy","year":2006,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Studentized range; Mathematics; Statistics; Statistic; Multivariate statistics; Confidence interval; Discretization; Edgeworth series; Studentized residual; Approximations of π; Poisson distribution; Poisson regression; Applied mathematics; Mathematical analysis; Standard error; Population","score_opus":0.20678167588250965,"score_gpt":0.44162457365300306,"score_spread":0.23484289777049341,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043630120","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0047128084,0.000011922648,0.98913515,0.00082930044,0.00005816593,0.0017065842,0.001343144,0.00003973052,0.0021631818],"genre_scores_gemma":[0.119290024,0.0000019565734,0.88012654,0.00007009968,0.000039477156,0.00034008647,0.000015461583,0.00002862558,0.00008774372],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980531,0.00003591591,0.00097017974,0.00024526383,0.00039246882,0.00030312466],"domain_scores_gemma":[0.9931568,0.004981904,0.00052935816,0.00061723357,0.0006063892,0.000108312335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004865973,0.00023854204,0.0005712508,0.000079445854,0.00015589526,0.000032026604,0.0004528568,0.00007258947,0.000035384444],"category_scores_gemma":[0.0061363694,0.0001517499,0.00011108443,0.0003301063,0.00045366463,0.00009238125,0.0001025448,0.00011112589,0.0000054327925],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003516084,0.0005768537,0.000023875153,0.001144218,0.000056852812,5.1176903e-7,0.00012350014,0.00026284828,0.0012740071,0.9923831,0.0014664894,0.0026525469],"study_design_scores_gemma":[0.00030003255,0.00016666256,0.0006476553,0.0003358819,0.00012330755,0.000006406919,0.00005607346,0.0053343573,0.0129933795,0.9787279,0.0011120428,0.00019634573],"about_ca_topic_score_codex":0.00008892862,"about_ca_topic_score_gemma":0.000028922512,"teacher_disagreement_score":0.11457721,"about_ca_system_score_codex":0.000013943001,"about_ca_system_score_gemma":0.000106570005,"threshold_uncertainty_score":0.73462504},"labels":[],"label_agreement":null},{"id":"W2050312253","doi":"10.1023/a:1004121503274","title":"Bivariate Sign Tests Based on the Sup, L1 and L2 Norms","year":2000,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Université de Montréal","funders":"","keywords":"Mathematics; Sign test; Bivariate analysis; Norm (philosophy); Sign (mathematics); Combinatorics; Univariate; Null hypothesis; Null distribution; Statistical hypothesis testing; Statistics; Mathematical analysis; Mann–Whitney U test; Multivariate statistics; Test statistic; Law; Wilcoxon signed-rank test","score_opus":0.17457271002756322,"score_gpt":0.4167402237277531,"score_spread":0.24216751370018988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050312253","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03866571,0.000026260526,0.94740075,0.0028229477,0.00008432876,0.0007162232,0.00063620764,0.000036909547,0.009610673],"genre_scores_gemma":[0.37488204,0.000036854475,0.6241585,0.00055190985,0.000027560101,0.000020474386,0.0000029576966,0.00003154843,0.00028818712],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979481,0.0001485279,0.00078168395,0.00024537553,0.0005596713,0.00031660445],"domain_scores_gemma":[0.9921396,0.0065339888,0.00029127634,0.00074131036,0.00017069797,0.00012313706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009658819,0.00026755818,0.0005793815,0.000045671408,0.00016509407,0.000025681205,0.00044365754,0.000094065166,0.0003105476],"category_scores_gemma":[0.005847046,0.00013960684,0.00011186583,0.00020818575,0.0008805819,0.0000896045,0.00008338581,0.0002442272,0.000011066076],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006440305,0.00040037234,0.0000067590604,0.00044452437,0.00004495417,0.0000052664245,0.00022799945,0.0009999692,0.000113852504,0.98418903,0.0012502763,0.012252562],"study_design_scores_gemma":[0.0002745714,0.00019190629,0.00017994097,0.0003917787,0.00007849195,0.000005677671,0.000035390356,0.05075915,0.0011701653,0.946165,0.0005784836,0.0001694011],"about_ca_topic_score_codex":0.000019997917,"about_ca_topic_score_gemma":0.0000054462635,"teacher_disagreement_score":0.33621633,"about_ca_system_score_codex":0.000009229639,"about_ca_system_score_gemma":0.00006558449,"threshold_uncertainty_score":0.69998825},"labels":[],"label_agreement":null},{"id":"W2056298903","doi":"10.1007/s10463-006-0090-4","title":"On weak convergence of random fields","year":2006,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Verifiable secret sharing; Mathematics; Stochastic process; Convergence (economics); Simple (philosophy); Applied mathematics; Process (computing); Mathematical optimization; Statistical physics; Computer science; Statistics","score_opus":0.06355185757525796,"score_gpt":0.2780131508831435,"score_spread":0.21446129330788555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056298903","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5152801,0.0002317992,0.46479902,0.00039426665,0.00036113846,0.0001949987,0.000542358,0.0000067457136,0.018189535],"genre_scores_gemma":[0.9844982,0.00005994548,0.0152170705,0.00004102849,0.000018903213,0.0000025701838,0.0000034635384,0.0000066998805,0.00015208594],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987545,0.000007922774,0.00091238494,0.00012102142,0.000080098645,0.00012408418],"domain_scores_gemma":[0.99881876,0.00026394054,0.00050045806,0.0003106729,0.000083456434,0.000022723289],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039199676,0.00009215888,0.00046083494,0.00005591442,0.000035724814,0.00000472445,0.00024389519,0.00006900595,0.00007351051],"category_scores_gemma":[0.0008995876,0.000075984084,0.00012338458,0.00012218268,0.0002404908,0.000061514715,0.00004724193,0.00008457639,0.000014155651],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033677672,0.00019787157,0.0006160063,0.00022933517,0.00001551449,2.8684576e-7,0.00008451535,0.0018735861,0.000030696672,0.99563587,0.0011122329,0.00017041867],"study_design_scores_gemma":[0.00031861142,0.000073209645,0.0021644789,0.00012692822,0.000008029847,4.3417256e-7,0.000010726283,0.022732513,0.0025889857,0.9713121,0.0005818726,0.0000820823],"about_ca_topic_score_codex":0.00044228867,"about_ca_topic_score_gemma":0.000027120934,"teacher_disagreement_score":0.4692181,"about_ca_system_score_codex":0.0000052106,"about_ca_system_score_gemma":0.000022642294,"threshold_uncertainty_score":0.3098541},"labels":[],"label_agreement":null},{"id":"W2060290814","doi":"10.1007/s10463-006-0038-8","title":"Waiting Time Distributions of Simple and Compound Patterns in a Sequence of r-th Order Markov Dependent Multi-state Trials","year":2006,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Manitoba","funders":"","keywords":"Markov chain; Mathematics; Independent and identically distributed random variables; Stochastic matrix; Sequence (biology); Discrete phase-type distribution; Continuous-time Markov chain; Applied mathematics; Geometric distribution; Probability distribution; Markov property; Markov model; Simple (philosophy); Eigenvalues and eigenvectors; Matrix (chemical analysis); Markov process; Markov chain mixing time; Combinatorics; Statistics; Random variable","score_opus":0.08048170647761914,"score_gpt":0.3362575385045916,"score_spread":0.25577583202697246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060290814","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82792944,0.000029309656,0.17042226,0.00016607008,0.00002899787,0.00026595054,0.0009014107,0.000009253625,0.00024734144],"genre_scores_gemma":[0.9829443,0.000010562809,0.016897727,0.000027277907,0.00001952684,0.0000044999724,0.000059518108,0.000010576724,0.000025988276],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981851,0.000050204762,0.0011894242,0.00013936995,0.00026870542,0.00016721757],"domain_scores_gemma":[0.9975028,0.0007396212,0.0011724896,0.00025287474,0.00032168496,0.000010496625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012564727,0.00014049873,0.000698268,0.0001193384,0.00005181674,0.000018558916,0.0002373789,0.000037003385,0.000041028674],"category_scores_gemma":[0.0027146528,0.00010552266,0.000089394955,0.0003397492,0.0003919854,0.00026071895,0.00019342717,0.000080453436,0.0000016528201],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016918802,0.001586419,0.006403794,0.0051466255,0.00030993676,0.000022481863,0.0002170835,0.024450243,0.02238748,0.9350247,0.00018655654,0.0040954934],"study_design_scores_gemma":[0.0012157051,0.000029920093,0.0042463583,0.0012271163,0.00038887642,0.0000046337,0.00022191564,0.21143167,0.009034123,0.77174425,0.00013917113,0.0003162824],"about_ca_topic_score_codex":0.0009547199,"about_ca_topic_score_gemma":0.0002838626,"teacher_disagreement_score":0.18698142,"about_ca_system_score_codex":0.000009588758,"about_ca_system_score_gemma":0.00002571472,"threshold_uncertainty_score":0.4303089},"labels":[],"label_agreement":null},{"id":"W2063410746","doi":"10.1007/bf02530500","title":"Strong consistency of automatic kernel regression estimates","year":2003,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Mathematics; Kernel regression; Independent and identically distributed random variables; Kernel (algebra); Bandwidth (computing); Bounded function; Consistency (knowledge bases); Statistics; Variable kernel density estimation; Applied mathematics; Strong consistency; Regression; Weak consistency; Kernel method; Random variable; Discrete mathematics; Computer science; Mathematical analysis; Artificial intelligence","score_opus":0.04805841346465264,"score_gpt":0.3353193986665352,"score_spread":0.2872609852018826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063410746","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.040002983,0.00014921605,0.95350707,0.00043282742,0.00031227065,0.00017277808,0.000032765787,0.00003945018,0.005350671],"genre_scores_gemma":[0.5169595,0.000008884742,0.4829479,0.000020583468,0.000004233623,0.0000018049001,8.2561854e-7,0.0000052105934,0.000051079936],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99851674,0.00007099256,0.00065160287,0.00015069844,0.00043269797,0.00017725395],"domain_scores_gemma":[0.9980581,0.0005374237,0.0005403102,0.0006108218,0.00019063073,0.000062704035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049954065,0.0001417302,0.0004203973,0.00005671091,0.00007193338,0.00001758413,0.0006637439,0.000047681464,0.000025085572],"category_scores_gemma":[0.0024833465,0.00008806592,0.00009915402,0.00022833896,0.0004054799,0.00013848562,0.00015463374,0.00012319315,0.0000043250934],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013188477,0.00022670063,0.00017178062,0.00072146836,0.000037066944,0.000003003738,0.00033772754,0.0004874648,0.0003177062,0.990758,0.00034742863,0.006590314],"study_design_scores_gemma":[0.0003507228,0.00020398018,0.0017155815,0.001690587,0.000056557827,0.000039150164,0.00008621871,0.40698445,0.02761238,0.5608168,0.00021882306,0.00022473295],"about_ca_topic_score_codex":0.000025527797,"about_ca_topic_score_gemma":0.0000011497116,"teacher_disagreement_score":0.4769565,"about_ca_system_score_codex":0.0000046277037,"about_ca_system_score_gemma":0.00011383563,"threshold_uncertainty_score":0.3591224},"labels":[],"label_agreement":null},{"id":"W2065950029","doi":"10.1007/bf02915436","title":"The empirical distribution function and partial sum process of residuals from a stationary arch with drift process","year":2005,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Brownian bridge; Mathematics; Ornstein–Uhlenbeck process; Gaussian process; Arch; Brownian excursion; Wiener process; Fractional Brownian motion; Brownian motion; Gaussian; Statistical physics; Mathematical analysis; Stationary process; Applied mathematics; Stochastic process; Statistics; Geometric Brownian motion; Diffusion process; Physics; Quantum mechanics; Computer science","score_opus":0.11052409613561902,"score_gpt":0.32909904050531424,"score_spread":0.2185749443696952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065950029","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79405254,0.00026993096,0.20294079,0.0010316442,0.00004905206,0.00020321547,0.001247218,0.0000054098073,0.00020022318],"genre_scores_gemma":[0.99428684,0.00008097734,0.005494019,0.00003190754,0.00003553793,0.0000123764985,0.000036901132,0.000007850374,0.0000136026965],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987634,0.000015371385,0.00077460555,0.0001654417,0.00013633934,0.00014486021],"domain_scores_gemma":[0.9987066,0.00031901026,0.00052150607,0.00021662735,0.00019703366,0.000039239578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004784286,0.00010248724,0.0003235774,0.000027273576,0.00012347713,0.000016041402,0.00016835358,0.00005847411,0.0000069228004],"category_scores_gemma":[0.0008030154,0.00006780092,0.00003989724,0.00015104386,0.00044348036,0.00017149323,0.000038526243,0.0001071934,0.0000017218455],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037298808,0.00049340015,0.02245535,0.0005684293,0.0001055753,3.9553976e-7,0.0023938706,0.0035132188,0.000022386092,0.9668205,0.00035610012,0.0028978141],"study_design_scores_gemma":[0.0004332954,0.00022654135,0.04925196,0.00021979694,0.00004333043,0.000001310683,0.00032557079,0.063862726,0.0014977782,0.8830891,0.0008931521,0.00015538973],"about_ca_topic_score_codex":0.00010274883,"about_ca_topic_score_gemma":0.00006264664,"teacher_disagreement_score":0.20023431,"about_ca_system_score_codex":0.000008624833,"about_ca_system_score_gemma":0.00007404069,"threshold_uncertainty_score":0.2764841},"labels":[],"label_agreement":null},{"id":"W2066996533","doi":"10.1007/s10463-013-0401-5","title":"One-armed bandit process with a covariate","year":2013,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland; University of Manitoba","funders":"","keywords":"Covariate; Mathematics; Conjugate prior; Bayesian probability; Statistics; Sequence (biology); Econometrics; Variance (accounting); Stochastic game; Monotonic function; Prior probability; Regression; Mathematical economics","score_opus":0.26697745204278833,"score_gpt":0.46407051248974257,"score_spread":0.19709306044695424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066996533","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10834079,0.000029989202,0.88440996,0.0025350896,0.00016020697,0.00094276,0.00021363774,0.000021910406,0.0033456224],"genre_scores_gemma":[0.87112486,0.000011178717,0.12820466,0.00010497494,0.000028772778,0.000039726532,0.000002679201,0.000017058652,0.000466082],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99592716,0.0000758432,0.00093424984,0.00027452942,0.002458032,0.0003301725],"domain_scores_gemma":[0.99506855,0.0017519797,0.0005624188,0.0008156496,0.0016522015,0.00014922774],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0011020553,0.00015958774,0.0005517335,0.00013393539,0.000108100525,0.00008661169,0.0012877783,0.00006283937,0.00050798117],"category_scores_gemma":[0.008446026,0.00008525093,0.000078372155,0.00078171864,0.0012651517,0.00047900894,0.00021665308,0.00019108459,0.00014619909],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057604804,0.0050323014,0.001218325,0.0025941578,0.0009053524,0.00005119371,0.006679902,0.022704553,0.0028759826,0.8262485,0.023969887,0.10714375],"study_design_scores_gemma":[0.00039679924,0.00021596666,0.0032752578,0.00023314182,0.000022738783,0.000009723478,0.00030681514,0.0110563245,0.008660091,0.97527647,0.0003925911,0.0001541087],"about_ca_topic_score_codex":0.000056240086,"about_ca_topic_score_gemma":0.000017609693,"teacher_disagreement_score":0.76278406,"about_ca_system_score_codex":0.000009980469,"about_ca_system_score_gemma":0.00020843737,"threshold_uncertainty_score":0.99990624},"labels":[],"label_agreement":null},{"id":"W2072856395","doi":"10.1007/s10463-008-0209-x","title":"A class of multi-sample nonparametric tests for panel count data","year":2008,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Nonparametric statistics; Mathematics; Statistics; Monte Carlo method; Count data; Sample (material); Sample size determination; Data set; Monotonic function; Panel data; Reliability (semiconductor); Statistical hypothesis testing; Applied mathematics","score_opus":0.5826455448929595,"score_gpt":0.47644908930935825,"score_spread":0.10619645558360125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072856395","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022765642,0.00006364211,0.9674482,0.00019920123,0.000208076,0.00071235385,0.008182032,0.00001841822,0.00040244948],"genre_scores_gemma":[0.1900382,0.000062914536,0.80969995,0.00005811437,0.0000235509,0.000018065934,0.000027953096,0.00002500921,0.00004623236],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972794,0.00007997618,0.0013877368,0.00029505874,0.0006347327,0.0003230703],"domain_scores_gemma":[0.9833241,0.013515107,0.0008760846,0.0014344844,0.0007351264,0.00011508083],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0011057698,0.00024333889,0.00095626165,0.0001053163,0.00010260364,0.0000090852955,0.0012055289,0.00012137869,0.000043467087],"category_scores_gemma":[0.06624226,0.00016642282,0.00013945355,0.0004292684,0.0012590216,0.00011323537,0.00040407683,0.00016105048,0.0000026910052],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005031329,0.001367985,0.000183012,0.0025246197,0.0001407655,0.0000031728546,0.00031828813,0.000028827008,0.0005354611,0.9858874,0.005429121,0.0035310418],"study_design_scores_gemma":[0.00070292485,0.00029571564,0.0013147992,0.00047330314,0.00019627609,0.0000196141,0.000071819,0.054835353,0.0051561114,0.9356059,0.0010795871,0.00024863917],"about_ca_topic_score_codex":0.00011372675,"about_ca_topic_score_gemma":0.000020735717,"teacher_disagreement_score":0.16727257,"about_ca_system_score_codex":0.000012326901,"about_ca_system_score_gemma":0.00021914318,"threshold_uncertainty_score":0.94162315},"labels":[],"label_agreement":null},{"id":"W2077591481","doi":"10.1023/a:1017517124707","title":"Laws of Iterated Logarithm and Related Asymptotics for Estimators of Conditional Density and Mode","year":2000,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Mathematics; Iterated logarithm; Estimator; Pointwise; Law of the iterated logarithm; Combinatorics; Asymptotic distribution; Iterated function; Logarithm; Conditional probability distribution; Rank (graph theory); Convergence of random variables; Pointwise convergence; Discrete mathematics; Random variable; Statistics; Mathematical analysis","score_opus":0.08751827537385182,"score_gpt":0.390211874850876,"score_spread":0.3026935994770242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2077591481","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5521651,0.000035957324,0.44441658,0.00019302986,0.000058281894,0.0004203593,0.0018934085,0.000010548813,0.00080671866],"genre_scores_gemma":[0.45953864,0.000022976268,0.54035544,0.000017979992,0.0000046652026,0.0000036184838,0.000009744385,0.000009919597,0.000037009715],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983374,0.000062499836,0.0009899385,0.00015687072,0.00029341344,0.00015988543],"domain_scores_gemma":[0.9961653,0.0025778895,0.00046731322,0.00026323742,0.00044454265,0.00008176643],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004815043,0.0001657911,0.00069769815,0.00004983648,0.000054841556,0.00000788822,0.00015764129,0.000112972186,0.00008604538],"category_scores_gemma":[0.003817848,0.00012047053,0.00007285588,0.00013089387,0.0012595451,0.00006730163,0.00006669936,0.000103385675,4.4384151e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060670372,0.00030989022,0.000073055606,0.0018118682,0.00012351846,0.0000014127071,0.0003418071,0.000071020615,0.00067951606,0.9932069,0.00028700652,0.0030333053],"study_design_scores_gemma":[0.00043354454,0.0001993663,0.0012862685,0.00044356036,0.00015801187,0.000019733188,0.00003101931,0.038384933,0.0102817975,0.94862795,0.00002297833,0.00011086739],"about_ca_topic_score_codex":0.000025716663,"about_ca_topic_score_gemma":0.0000029248076,"teacher_disagreement_score":0.09593884,"about_ca_system_score_codex":0.0000046274326,"about_ca_system_score_gemma":0.00006254038,"threshold_uncertainty_score":0.49126458},"labels":[],"label_agreement":null},{"id":"W2089059576","doi":"10.1007/s10463-014-0490-9","title":"Parameterizing mixture models with generalized moments","year":2014,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mixing (physics); Mathematics; Moment (physics); Space (punctuation); Parameter space; Distribution (mathematics); Curse of dimensionality; Applied mathematics; Generalized method of moments; Mixture model; Dimensionality reduction; Second moment of area; Statistical physics; Mathematical analysis; Statistics; Geometry; Computer science; Classical mechanics; Physics","score_opus":0.061794282657489374,"score_gpt":0.31015294677653404,"score_spread":0.24835866411904467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089059576","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008855085,0.000028255014,0.9874761,0.0007946749,0.00014628808,0.00017536811,0.00002263509,0.000022559352,0.0024790515],"genre_scores_gemma":[0.22159615,0.000012485927,0.77799714,0.00030861594,0.000014141224,0.0000057234292,0.000001060535,0.0000087229655,0.000055988086],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986181,0.000095763164,0.0004343194,0.00020812836,0.00042421775,0.00021945928],"domain_scores_gemma":[0.9984619,0.00021726885,0.00029993936,0.0007643695,0.00016876118,0.0000877726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005262879,0.0001641299,0.00041332302,0.000046234632,0.00006533995,0.000036679296,0.0008993867,0.00006226825,0.0000031723175],"category_scores_gemma":[0.00021318512,0.0000950251,0.00008009865,0.00021095741,0.0002459406,0.00027346762,0.00021498998,0.00011045796,0.0000014024406],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008261947,0.00010349129,0.0000027601068,0.00017178782,0.000041898118,0.0000014822336,0.00030090776,0.0007739961,0.00068646274,0.98774207,0.00033704174,0.00982984],"study_design_scores_gemma":[0.00019976706,0.00009291608,0.00002098598,0.00017114524,0.000020887166,0.0000094898,0.0000026086254,0.19496734,0.0073131924,0.79682237,0.00026696545,0.000112310234],"about_ca_topic_score_codex":0.000015311565,"about_ca_topic_score_gemma":0.0000024057363,"teacher_disagreement_score":0.21274106,"about_ca_system_score_codex":0.000004778114,"about_ca_system_score_gemma":0.00004815677,"threshold_uncertainty_score":0.3875011},"labels":[],"label_agreement":null},{"id":"W2089248328","doi":"10.1007/s10463-011-0337-6","title":"Tests of symmetry for bivariate copulas","year":2011,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":112,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; McGill University","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Mathematics; Copula (linguistics); Bivariate analysis; Statistics; Applied mathematics; Econometrics","score_opus":0.2073227284697281,"score_gpt":0.3159335182575282,"score_spread":0.10861078978780009,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089248328","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37794766,0.0003036177,0.6115013,0.00015179449,0.0004663094,0.00044102082,0.0021391427,0.000010380034,0.0070388042],"genre_scores_gemma":[0.8096517,0.000042305728,0.19020286,0.000028761075,0.000013601184,0.0000055440337,0.0000038851563,0.000010426781,0.000040933865],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986308,0.000005981494,0.0010127492,0.0001372799,0.000058000947,0.0001551938],"domain_scores_gemma":[0.99858564,0.0001929329,0.0006809317,0.00035460823,0.00014782227,0.000038089733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005507297,0.00010259382,0.0005204479,0.000079295554,0.000039656396,0.0000040259342,0.00030873003,0.000073624295,0.00003792063],"category_scores_gemma":[0.001866993,0.00008684946,0.00014528686,0.00015038872,0.00024722118,0.00009100129,0.00007341202,0.00006319422,0.000006827793],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025255593,0.00026339467,0.0016548588,0.00059593056,0.000041990173,1.9754184e-7,0.0004745427,0.000022036653,0.000051082247,0.9960191,0.00024480504,0.0006067557],"study_design_scores_gemma":[0.0001963341,0.000114488,0.006307724,0.00013295886,0.000018664336,6.0098216e-7,0.000023334316,0.0065703033,0.0033858598,0.9827744,0.00038130273,0.000094041825],"about_ca_topic_score_codex":0.0002765294,"about_ca_topic_score_gemma":0.000015881114,"teacher_disagreement_score":0.431704,"about_ca_system_score_codex":0.0000059721515,"about_ca_system_score_gemma":0.00003185468,"threshold_uncertainty_score":0.35416183},"labels":[],"label_agreement":null},{"id":"W2089695579","doi":"10.1023/a:1004137016101","title":"A Stochastic Advection-Diffusion Model for the Rocky Flats Soil Plutonium Data","year":2000,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Advection; Mathematics; Covariance; Diffusion; Covariance function; Goodness of fit; Stochastic modelling; Statistics; Meteorology; Geography; Physics","score_opus":0.08345368842997615,"score_gpt":0.31806878650703974,"score_spread":0.2346150980770636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089695579","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025032489,0.0000353432,0.9705455,0.0008737995,0.00018132155,0.0005234006,0.0010353535,0.000013950874,0.0017588526],"genre_scores_gemma":[0.9021772,0.00008803121,0.09602268,0.00031646545,0.00004465421,0.000033249675,0.000043422075,0.000025140804,0.0012491522],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99861956,0.000015746144,0.00047225016,0.00022712034,0.00042783588,0.00023747401],"domain_scores_gemma":[0.99825585,0.00059421774,0.00019822906,0.000845654,0.00004018335,0.00006586396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040751934,0.00014710211,0.00024127381,0.00001557646,0.00024562812,0.00001924638,0.0008665966,0.000051975425,0.0002666952],"category_scores_gemma":[0.00074356876,0.000088490975,0.000064193766,0.00014112663,0.0005337236,0.00013960322,0.0003954587,0.00010351116,0.000027851864],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001096481,0.000595051,0.000031485928,0.0003626783,0.00011964713,0.0000014795495,0.0014455257,0.8178397,0.00079419365,0.09714827,0.027717607,0.053834718],"study_design_scores_gemma":[0.00017952167,0.000035065477,0.00037927402,0.00008118208,0.000073875315,0.0000044721246,0.00003874835,0.8843029,0.00012621569,0.113356486,0.0013213689,0.00010086882],"about_ca_topic_score_codex":0.00026603474,"about_ca_topic_score_gemma":0.00018229705,"teacher_disagreement_score":0.8771447,"about_ca_system_score_codex":0.000014409275,"about_ca_system_score_gemma":0.00004346589,"threshold_uncertainty_score":0.36085573},"labels":[],"label_agreement":null},{"id":"W2093972316","doi":"10.1007/s10463-006-0042-z","title":"Wavelet-Based Estimation for Univariate Stable Laws","year":2006,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Wavelet; Univariate; Context (archaeology); Parametric statistics; Algorithm; Mathematics; Domain (mathematical analysis); Computer science; Inference; Mathematical optimization; Artificial intelligence; Statistics; Multivariate statistics","score_opus":0.05950508309257805,"score_gpt":0.33506851357566486,"score_spread":0.2755634304830868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093972316","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015301125,0.000019152467,0.99553746,0.0010475141,0.00019141253,0.0002446238,0.000079533675,0.000025124209,0.0013250761],"genre_scores_gemma":[0.118996665,0.0000010501909,0.8806737,0.00013724688,0.000017747596,0.0000067369383,0.0000072302014,0.000007543377,0.0001520478],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988199,0.000051959854,0.00048785572,0.0001440951,0.00030604945,0.00019012832],"domain_scores_gemma":[0.99824274,0.000672084,0.00028905983,0.00047286545,0.00028941472,0.0000338526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072857377,0.000113865266,0.0002750913,0.000056087774,0.000093488336,0.000045685956,0.0006038402,0.000047172012,0.0000047560984],"category_scores_gemma":[0.0006877717,0.00008135163,0.00009190986,0.00022919795,0.00018398133,0.00022630856,0.00008515048,0.0000584008,0.0000026204427],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012975481,0.00017850325,0.000001288315,0.00033434873,0.000012457332,0.0000016141596,0.000045667068,0.003872801,0.0019630925,0.9843035,0.0020774833,0.0071962844],"study_design_scores_gemma":[0.00027828696,0.000054991597,0.000089101886,0.000100288475,0.000016828746,0.0000017655317,0.0000019846161,0.3746609,0.046457704,0.5776146,0.00064716575,0.00007636952],"about_ca_topic_score_codex":0.000083116756,"about_ca_topic_score_gemma":0.0000046165337,"teacher_disagreement_score":0.40668887,"about_ca_system_score_codex":0.00000929907,"about_ca_system_score_gemma":0.0001249048,"threshold_uncertainty_score":0.33174232},"labels":[],"label_agreement":null},{"id":"W2104550218","doi":"10.1007/s10463-010-0319-0","title":"Instrumental variable approach to covariate measurement error in generalized linear models","year":2010,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Estimator; Covariate; Mathematics; Instrumental variable; Nonparametric statistics; Applied mathematics; Parametric statistics; Observational error; Statistics; Variable (mathematics); Errors-in-variables models; Asymptotic distribution; Generalized linear model; Econometrics; Mathematical analysis","score_opus":0.26574496962159494,"score_gpt":0.4000895641791143,"score_spread":0.13434459455751935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104550218","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025125101,0.0000055525484,0.9644558,0.00027983295,0.00035627896,0.0006992842,0.00035064158,0.000021020564,0.00870652],"genre_scores_gemma":[0.21803255,0.0000031424781,0.7817223,0.00012592974,0.000029472467,0.000037139514,0.0000035231456,0.000023613939,0.00002229166],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970783,0.00012233053,0.0012015164,0.00029794886,0.0009132417,0.0003866435],"domain_scores_gemma":[0.9977567,0.00057322334,0.00036512362,0.00070855813,0.0004108331,0.00018556518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019618522,0.00027133338,0.000784644,0.000118556425,0.000071015624,0.00002315376,0.0006658821,0.00014449818,0.00006920494],"category_scores_gemma":[0.0057666763,0.00019034786,0.000103998645,0.00043855715,0.00037258727,0.00013890113,0.00025301953,0.00036589504,0.0000051615402],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004981648,0.0010379938,0.000017350358,0.0006703611,0.000057106965,0.0000017760754,0.00040224456,0.00030622358,0.0046678204,0.9910176,0.0005023269,0.0012694077],"study_design_scores_gemma":[0.00046205593,0.00007545375,0.000119367956,0.00027041096,0.00005577841,0.000008614985,0.00004982974,0.049907696,0.0048858244,0.94382924,0.00012877087,0.00020693084],"about_ca_topic_score_codex":0.00017562216,"about_ca_topic_score_gemma":0.000048095822,"teacher_disagreement_score":0.19290745,"about_ca_system_score_codex":0.000025510384,"about_ca_system_score_gemma":0.00019821609,"threshold_uncertainty_score":0.77621603},"labels":[],"label_agreement":null},{"id":"W2104919849","doi":"10.1007/s10463-006-0033-0","title":"Classification of Three-word Indicator Functions of Two-level Factorial Designs","year":2006,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Prince Edward Island; McMaster University","funders":"","keywords":"Fractional factorial design; Mathematics; Factorial experiment; Factorial; Function (biology); Statistics; Word (group theory); Mathematical analysis; Geometry","score_opus":0.44937214145692117,"score_gpt":0.4780368278204825,"score_spread":0.028664686363561342,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104919849","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14912385,0.000038107253,0.8459705,0.00013146245,0.0005445405,0.0003307547,0.000716012,0.000008182311,0.0031365985],"genre_scores_gemma":[0.6323515,0.000002016016,0.36750123,0.00000787628,0.000036963673,0.00000571695,0.0000050724507,0.000008579758,0.000080995225],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9959872,0.00019287782,0.0018329088,0.00023793434,0.0015668358,0.00018228972],"domain_scores_gemma":[0.9942888,0.002670191,0.0015532102,0.0007848296,0.0006326008,0.000070343485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002150216,0.00016815358,0.00065754354,0.00019520795,0.00007061287,0.0000207593,0.00090204837,0.00009968897,0.00017645578],"category_scores_gemma":[0.004875929,0.00010948857,0.00020290699,0.00063378527,0.0012194656,0.00021089533,0.00015999451,0.00011961719,0.000016913156],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000098135664,0.0009350921,0.0014622081,0.00012442985,0.00006523931,6.493009e-7,0.00024263213,0.0006199382,0.14261404,0.84660053,0.0028147637,0.0044223503],"study_design_scores_gemma":[0.0004450086,0.00021855459,0.0286284,0.0001220967,0.000075661555,0.0000028387556,0.00020586421,0.0036262113,0.17724495,0.78903204,0.000248584,0.00014980507],"about_ca_topic_score_codex":0.00016981018,"about_ca_topic_score_gemma":0.000034292934,"teacher_disagreement_score":0.4832277,"about_ca_system_score_codex":0.000016265114,"about_ca_system_score_gemma":0.00018599494,"threshold_uncertainty_score":0.5837295},"labels":[],"label_agreement":null},{"id":"W2106285054","doi":"10.1007/s10463-013-0442-9","title":"Generalized duration models and optimal estimation using estimating functions","year":2014,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Mathematics; Applied mathematics; Multiplicative function; Conditional expectation; Autoregressive model; Inference; Martingale (probability theory); Statistics; Computer science","score_opus":0.1370417022427369,"score_gpt":0.31227303934550005,"score_spread":0.17523133710276315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106285054","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33254048,0.00004768821,0.6665755,0.00013971142,0.00014259099,0.00009629331,0.00008799981,0.0000070285914,0.00036272345],"genre_scores_gemma":[0.5528116,0.00000813452,0.44711497,0.000019820767,0.000018975468,0.0000021427534,0.000005008931,0.0000063134326,0.000012998204],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998818,0.000013979019,0.00082389306,0.00015041979,0.000068866306,0.00012486281],"domain_scores_gemma":[0.9990167,0.00011509753,0.0005132234,0.0002248145,0.00009185587,0.000038287813],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006077002,0.00010207183,0.0003439347,0.000069522524,0.00013267966,0.000024617795,0.00011051765,0.00006067657,0.000009042144],"category_scores_gemma":[0.0011831268,0.000091868176,0.000058460988,0.00011587889,0.00017267147,0.00029218054,0.000061365885,0.00007351342,0.0000030905842],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005520005,0.000043222422,0.00008401078,0.00015259894,0.000012610136,5.376577e-8,0.00023633117,0.26268566,0.000057849527,0.73560166,0.00003337138,0.0010870772],"study_design_scores_gemma":[0.00009015267,0.000018446946,0.00014309515,0.00005617294,0.000009937,0.0000013608613,0.000008843149,0.59952646,0.00010845286,0.3999531,0.000029874278,0.00005409443],"about_ca_topic_score_codex":0.00016795457,"about_ca_topic_score_gemma":0.0000059617205,"teacher_disagreement_score":0.3368408,"about_ca_system_score_codex":0.000010354101,"about_ca_system_score_gemma":0.00002020736,"threshold_uncertainty_score":0.37462753},"labels":[],"label_agreement":null},{"id":"W2112767862","doi":"10.1007/s10463-010-0309-2","title":"A sequential order statistics approach to step-stress testing","year":2010,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Statistics; Estimator; Maximum likelihood; Stress (linguistics); Order statistic; Applied mathematics","score_opus":0.1819410566367363,"score_gpt":0.40455571901058834,"score_spread":0.22261466237385205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112767862","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010256567,0.0000022648792,0.9741193,0.00045532937,0.00024726722,0.00066957495,0.005921791,0.00005343526,0.008274471],"genre_scores_gemma":[0.25082344,9.520619e-7,0.74876654,0.00011183335,0.0000416692,0.000047529866,0.0000634998,0.000025141224,0.00011936394],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975239,0.000052436953,0.0011033029,0.000277168,0.00070507836,0.00033810665],"domain_scores_gemma":[0.99561614,0.0016588577,0.0005176564,0.00077034946,0.0011991763,0.00023783487],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00052022096,0.00025528483,0.000519273,0.000082523,0.00017707849,0.00004126264,0.0006523791,0.000121224366,0.00013128015],"category_scores_gemma":[0.016591491,0.00019218292,0.00008202199,0.00070928154,0.0007136682,0.00009365581,0.00022269359,0.00033399885,0.000029240806],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009992718,0.00089294906,0.00003233664,0.0006561225,0.0000481228,0.0000010763081,0.00016239451,0.0001260211,0.0020164114,0.984844,0.009358455,0.001852093],"study_design_scores_gemma":[0.00041506006,0.000088138666,0.0012393069,0.00023650966,0.000172778,0.000027004238,0.00013443906,0.041243594,0.007560069,0.9469151,0.0015829068,0.0003850741],"about_ca_topic_score_codex":0.000049589056,"about_ca_topic_score_gemma":0.00002730605,"teacher_disagreement_score":0.24056688,"about_ca_system_score_codex":0.000012724357,"about_ca_system_score_gemma":0.00019368768,"threshold_uncertainty_score":0.9916922},"labels":[],"label_agreement":null},{"id":"W2114959612","doi":"10.1007/s10463-006-0075-3","title":"On constrained generalized inverses of matrices and their properties","year":2006,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Mathematics; Pure mathematics; Applied mathematics","score_opus":0.04436942490366452,"score_gpt":0.2699079812584746,"score_spread":0.22553855635481007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114959612","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52175814,0.00028867985,0.4729806,0.0008775229,0.00020975289,0.0003262817,0.00018656717,0.0000322683,0.0033401786],"genre_scores_gemma":[0.9018089,0.000030795047,0.098009884,0.00006856814,0.000012940294,0.0000025904897,9.709778e-7,0.0000043473037,0.000060990307],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990857,0.000046697493,0.000432784,0.00011574028,0.00020271327,0.00011636163],"domain_scores_gemma":[0.99894404,0.0003028492,0.00028966597,0.00031354316,0.0001193233,0.000030548174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000288564,0.00011670991,0.00031441892,0.000054017237,0.000049016286,0.000018549546,0.0004477648,0.000035454403,0.000007791456],"category_scores_gemma":[0.00025599537,0.0000642927,0.000059286274,0.0001494885,0.00058528996,0.00012709544,0.00014580929,0.000052216816,0.0000010707586],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000108635795,0.00015364695,0.0000058746473,0.00039746848,0.000023797276,0.0000011276475,0.00024388335,0.00020849972,0.002566185,0.9946102,0.0003000965,0.0014783619],"study_design_scores_gemma":[0.000236143,0.00011605061,0.00006825677,0.0002764725,0.000012917455,0.0000075985395,0.000050371007,0.02048262,0.10718111,0.8713301,0.00014127837,0.0000971182],"about_ca_topic_score_codex":0.000042301905,"about_ca_topic_score_gemma":0.0000029136402,"teacher_disagreement_score":0.38005075,"about_ca_system_score_codex":0.0000022036206,"about_ca_system_score_gemma":0.000046328045,"threshold_uncertainty_score":0.26217803},"labels":[],"label_agreement":null},{"id":"W2130541178","doi":"10.1007/s10463-010-0300-y","title":"Distribution and double generating function of number of patterns in a sequence of Markov dependent multistate trials","year":2010,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Advanced Combinatorial Mathematics","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Mathematics; Sequence (biology); Generating function; Markov chain; Probability distribution; Statistics; Function (biology); Distribution (mathematics); Applied mathematics; Combinatorics; Discrete mathematics; Mathematical analysis","score_opus":0.12810477797317443,"score_gpt":0.4046821453628474,"score_spread":0.276577367389673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130541178","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8124304,0.000011255363,0.18561067,0.0000373321,0.00026865065,0.000541601,0.0009446132,0.0000073635133,0.00014815335],"genre_scores_gemma":[0.82946897,0.00002842079,0.17042255,0.0000034329428,0.00001669457,0.000014102459,0.000014392834,0.000017846185,0.000013582216],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99655634,0.00012022346,0.0023516333,0.00018183725,0.0005887308,0.00020126035],"domain_scores_gemma":[0.99448884,0.0020416214,0.0023361724,0.0005537908,0.00052016095,0.000059423277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020675194,0.00021524986,0.0012094986,0.00006533881,0.000033083725,0.000007485286,0.00030793564,0.00013968427,0.000030954252],"category_scores_gemma":[0.006903925,0.00016151348,0.00013552964,0.00021794581,0.0005024906,0.0001618953,0.00018542017,0.0002298225,4.205712e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017545625,0.00077657617,0.0008156924,0.0050304434,0.00010410183,0.000002079957,0.00056313374,0.00010199356,0.062372204,0.92859054,0.00003072977,0.0014370804],"study_design_scores_gemma":[0.0013383742,0.00012627816,0.0005087702,0.0011018078,0.00017231722,0.000012272988,0.00018528177,0.0028794005,0.15695329,0.83655316,0.000009422927,0.00015966166],"about_ca_topic_score_codex":0.00012221631,"about_ca_topic_score_gemma":0.00009337401,"teacher_disagreement_score":0.09458108,"about_ca_system_score_codex":0.000015422915,"about_ca_system_score_gemma":0.000090614165,"threshold_uncertainty_score":0.8265142},"labels":[],"label_agreement":null},{"id":"W2149205892","doi":"10.1007/s10463-011-0339-4","title":"On estimating distribution functions using Bernstein polynomials","year":2011,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Control Systems and Identification","field":"Engineering","cited_by":94,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Mathematics; Estimator; Pointwise; Bernstein polynomial; Asymptotic distribution; Empirical distribution function; Applied mathematics; Mean squared error; Polynomial; Distribution function; Boundary (topology); Distribution (mathematics); Function (biology); Statistics; Mathematical analysis","score_opus":0.08523484375542627,"score_gpt":0.28829145529190303,"score_spread":0.20305661153647675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149205892","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2917578,0.000025311883,0.70530635,0.000026386726,0.0007025884,0.00019024739,0.00035021908,0.000031664902,0.0016094593],"genre_scores_gemma":[0.9764178,0.0000021493715,0.023482395,0.000004821168,0.000034361092,0.000005104308,0.000012639381,0.000011232887,0.00002949045],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991366,0.000015471564,0.0004900806,0.00007293922,0.000171093,0.00011380322],"domain_scores_gemma":[0.99934465,0.0000982308,0.00016448548,0.00026295232,0.000093958195,0.00003574982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017810673,0.00009483369,0.0002169798,0.000031367785,0.00006016561,0.000010366846,0.00013394104,0.000044229175,0.000026769649],"category_scores_gemma":[0.0004281933,0.00007239755,0.00006518023,0.00010492269,0.00009979782,0.00009339659,0.000023802364,0.00006428295,0.000010196377],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003175029,0.0003538084,0.00008331671,0.0015300856,0.0002458043,0.0000027069204,0.0009587825,0.047983542,0.020484172,0.9159385,0.004791338,0.0075962213],"study_design_scores_gemma":[0.00040129144,0.00011085673,0.0029047604,0.0012513684,0.00018779542,0.000017687666,0.0001409704,0.8409319,0.026266105,0.12713373,0.00032871726,0.00032481257],"about_ca_topic_score_codex":0.00010794024,"about_ca_topic_score_gemma":0.0000099731515,"teacher_disagreement_score":0.79294837,"about_ca_system_score_codex":0.0000177478,"about_ca_system_score_gemma":0.000017031929,"threshold_uncertainty_score":0.29522866},"labels":[],"label_agreement":null},{"id":"W2157808098","doi":"10.1007/s10463-013-0441-x","title":"Estimation of the error density in a semiparametric transformation model","year":2014,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre hospitalier universitaire de Québec","funders":"Science and Technology Facilities Council","keywords":"Mathematics; Estimator; Kernel density estimation; Kernel (algebra); Transformation (genetics); Nonparametric statistics; Lambda; Applied mathematics; Type (biology); Semiparametric model; Asymptotic distribution; Combinatorics; Statistics; Physics","score_opus":0.16173251321971743,"score_gpt":0.40438957375646567,"score_spread":0.24265706053674824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157808098","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28464928,0.0000050187205,0.7130088,0.00029366632,0.00008130639,0.00031623986,0.000097733704,0.0000072752177,0.0015406483],"genre_scores_gemma":[0.61192745,0.0000033337992,0.38799995,0.000038856335,0.0000039916863,0.0000059048493,0.0000011310568,0.000007721207,0.000011665841],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978029,0.00016145117,0.0011401466,0.00013346742,0.00056870165,0.00019330624],"domain_scores_gemma":[0.9963212,0.0022244279,0.00061881356,0.0005457391,0.00023946507,0.000050377108],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0013331647,0.00016392033,0.00056661124,0.000099957695,0.000054638276,0.000008501873,0.00046154598,0.00010131927,0.000012311263],"category_scores_gemma":[0.015138384,0.0000973633,0.00012935164,0.00052442227,0.0005015942,0.00010962853,0.000097232994,0.0001918624,0.0000014646766],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001866641,0.00030273982,0.00006189375,0.0012455238,0.000018842979,1.3734586e-7,0.00085894344,0.0078841355,0.00032367703,0.98098695,0.00013746947,0.008161046],"study_design_scores_gemma":[0.00014091142,0.00003494027,0.0008853064,0.0003056575,0.000039004008,0.0000016964772,0.000027441976,0.42451444,0.008490817,0.56549567,0.000003874439,0.000060224353],"about_ca_topic_score_codex":0.000046009158,"about_ca_topic_score_gemma":0.000027014408,"teacher_disagreement_score":0.41663033,"about_ca_system_score_codex":0.000016365295,"about_ca_system_score_gemma":0.00008601477,"threshold_uncertainty_score":0.9931575},"labels":[],"label_agreement":null},{"id":"W2161637756","doi":"10.1007/s10463-006-0051-y","title":"Asymptotic Normality of the Recursive M-estimators of the Scale Parameters","year":2006,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Mathematics; Estimator; Normality; Asymptotic distribution; Scale (ratio); Statistics; Scale parameter; Local asymptotic normality; Applied mathematics; Econometrics; Geography","score_opus":0.11763633290042387,"score_gpt":0.3995819590045093,"score_spread":0.28194562610408547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161637756","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27368075,0.000039855808,0.7211422,0.0006430409,0.00041087944,0.0007913291,0.0010471278,0.000012886311,0.0022319544],"genre_scores_gemma":[0.49879092,0.0000070677593,0.5010239,0.000046512836,0.0000122438205,0.000008526164,0.0000014946369,0.000019715872,0.000089615816],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9968023,0.00025630352,0.0015426673,0.00021917278,0.00085938204,0.00032021754],"domain_scores_gemma":[0.9937079,0.003067754,0.001491282,0.0011745634,0.0004891561,0.000069345675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000912913,0.00026949498,0.00087194255,0.000041198968,0.00012881539,0.000008481361,0.0009887869,0.00012131406,0.000018087263],"category_scores_gemma":[0.0069145197,0.0001376523,0.00037258654,0.00039442242,0.0023798451,0.00010163362,0.00037318634,0.0002594222,9.885719e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003199316,0.00059193355,0.00032159904,0.0015126418,0.00008326928,7.2595526e-7,0.00033681365,0.0014373452,0.0008492917,0.9932183,0.00088072906,0.0007353267],"study_design_scores_gemma":[0.00023905312,0.00007244096,0.0023240903,0.0008147163,0.00022871303,0.000007161861,0.00009151311,0.002122283,0.050632864,0.9432748,0.000051345833,0.00014099806],"about_ca_topic_score_codex":0.00013868463,"about_ca_topic_score_gemma":0.00004721578,"teacher_disagreement_score":0.22511017,"about_ca_system_score_codex":0.000021525319,"about_ca_system_score_gemma":0.00013960047,"threshold_uncertainty_score":0.87686384},"labels":[],"label_agreement":null},{"id":"W2163009348","doi":"10.1007/s10463-008-0170-8","title":"Proportional hazards regression under progressive Type-II censoring","year":2008,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Censoring (clinical trials); Mathematics; Estimator; Statistics; Proportional hazards model; Monte Carlo method; Econometrics; Martingale (probability theory)","score_opus":0.208747829864109,"score_gpt":0.42691362102306163,"score_spread":0.21816579115895263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163009348","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2118008,0.000067573994,0.7784013,0.002678976,0.0003136748,0.00083266513,0.0009247319,0.00008498382,0.004895295],"genre_scores_gemma":[0.8087953,0.000021304171,0.19066574,0.00008088782,0.000033866603,0.000025379697,0.000040655184,0.000017564655,0.00031934516],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980161,0.00004009111,0.000845736,0.00018656183,0.0006921481,0.00021936119],"domain_scores_gemma":[0.99762243,0.0004736819,0.0005950087,0.00045837695,0.0007388449,0.00011163249],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024262881,0.0001837347,0.00039645695,0.00005097947,0.00033299398,0.000008078466,0.00031933794,0.000089694884,0.00029920513],"category_scores_gemma":[0.0033959479,0.00011972357,0.00010988646,0.00034122917,0.0009778251,0.000107714885,0.00016039332,0.00016038954,0.000016529935],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001939812,0.0006405204,0.000038084978,0.00029136427,0.00004738104,0.0000043265654,0.00017113824,0.00006503474,0.0003336495,0.9882668,0.009611306,0.0005109942],"study_design_scores_gemma":[0.00031614114,0.00010905731,0.004074771,0.00047211704,0.00007339629,0.000074012736,0.000078895435,0.003714001,0.010262176,0.97975826,0.00086457597,0.0002026029],"about_ca_topic_score_codex":0.000005710254,"about_ca_topic_score_gemma":0.0000010890344,"teacher_disagreement_score":0.59699446,"about_ca_system_score_codex":0.000021340411,"about_ca_system_score_gemma":0.00021167983,"threshold_uncertainty_score":0.48821855},"labels":[],"label_agreement":null},{"id":"W2474434266","doi":"10.1007/s10463-016-0569-6","title":"On the identifiability of start-up demonstration mixture models","year":2016,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Fonds National de la Recherche Luxembourg","keywords":"Identifiability; Mathematics; Binary number; Component (thermodynamics); Start up; Quality (philosophy); Algorithm; Computer science; Mathematical optimization; Applied mathematics; Statistics; Arithmetic","score_opus":0.1736657261290341,"score_gpt":0.3838608491457501,"score_spread":0.21019512301671597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2474434266","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06294548,0.0000058440664,0.92835575,0.004119351,0.00011600008,0.0005152059,0.0018561893,0.000019534402,0.0020666278],"genre_scores_gemma":[0.9627431,0.000010115373,0.036957923,0.00008560617,0.000010678067,0.000029358376,0.000010102548,0.000011652633,0.00014148494],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979526,0.000100984165,0.0009957968,0.0001709165,0.0006092157,0.00017050645],"domain_scores_gemma":[0.9937531,0.004230866,0.0006305041,0.00076070643,0.00055494293,0.00006987633],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0007159517,0.00016288912,0.0003726477,0.00003670692,0.00010801192,0.000011394526,0.0004505147,0.00008273763,0.0002267499],"category_scores_gemma":[0.008506638,0.00007757444,0.00014235686,0.0002309284,0.0011061011,0.0001257968,0.000079759484,0.000106208856,0.000012237609],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021286067,0.00039223887,0.000006600881,0.00025717774,0.000043901175,1.7496832e-7,0.00012558135,0.000053608557,0.0016606521,0.98868,0.0077576223,0.001001152],"study_design_scores_gemma":[0.00018315628,0.00004770645,0.0003068771,0.00032909904,0.0000597425,0.0000016515322,0.00005408092,0.0043880534,0.021043407,0.9734299,0.00006926141,0.00008703165],"about_ca_topic_score_codex":0.000009046795,"about_ca_topic_score_gemma":0.000009123635,"teacher_disagreement_score":0.8997976,"about_ca_system_score_codex":0.000017204937,"about_ca_system_score_gemma":0.00009235829,"threshold_uncertainty_score":0.99984515},"labels":[],"label_agreement":null},{"id":"W2531934726","doi":"10.1007/s10463-017-0610-4","title":"Inference for a change-point problem under a generalised Ornstein–Uhlenbeck setting","year":2017,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor; Western University","funders":"Philippine Council for Industry, Energy, and Emerging Technology Research and Development; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Fields Institute for Research in Mathematical Sciences","keywords":"Ornstein–Uhlenbeck process; Mathematics; Inference; Equivalence (formal languages); Point process; Series (stratigraphy); Point (geometry); Change detection; Applied mathematics; Point estimation; Maximum likelihood; Econometrics; Statistics; Stochastic process; Computer science; Artificial intelligence; Discrete mathematics","score_opus":0.33491191857799485,"score_gpt":0.3563879401145589,"score_spread":0.021476021536564027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2531934726","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5759034,0.00036607945,0.37697178,0.018278793,0.0010875927,0.0023741508,0.006596442,0.00003714353,0.018384596],"genre_scores_gemma":[0.92177504,0.000059872305,0.07734608,0.0004641381,0.000093285635,0.00004223208,0.000010397525,0.000017672237,0.00019125086],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985643,0.000008116482,0.0008901907,0.00020508509,0.000046418456,0.00028590404],"domain_scores_gemma":[0.9977149,0.00018594666,0.001244339,0.0007272263,0.000049619477,0.00007796309],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006650786,0.00015816138,0.00056176964,0.000064572996,0.00021872268,0.0000658405,0.00056189054,0.00008075323,0.00007242259],"category_scores_gemma":[0.0012070767,0.00013294656,0.00015850483,0.000033664463,0.0003475526,0.00037581712,0.00016153608,0.00008651149,0.000026882853],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018003668,0.00012488729,0.00070676336,0.0006172953,0.000111413334,4.976808e-7,0.00060311623,0.0007706119,0.000043355296,0.99471223,0.0014504397,0.0008414093],"study_design_scores_gemma":[0.00046822714,0.000105886254,0.00601513,0.0002285359,0.000022085653,0.0000028326833,0.000032494987,0.0417817,0.0008764329,0.9484658,0.0017911796,0.00020964658],"about_ca_topic_score_codex":0.0005458793,"about_ca_topic_score_gemma":0.000049288148,"teacher_disagreement_score":0.34587166,"about_ca_system_score_codex":0.000016048525,"about_ca_system_score_gemma":0.000027571925,"threshold_uncertainty_score":0.5421403},"labels":[],"label_agreement":null},{"id":"W2550654637","doi":"10.1007/s10463-016-0590-9","title":"Inferences in semi-parametric dynamic mixed models for longitudinal count data","year":2016,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Mathematics; Estimator; Parametric statistics; Count data; Random effects model; Consistency (knowledge bases); Statistics; Quasi-likelihood; Strong consistency; Applied mathematics; Poisson distribution; Econometrics","score_opus":0.30337942978221777,"score_gpt":0.4466509848132453,"score_spread":0.1432715550310275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2550654637","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016089188,0.000048733473,0.97853625,0.0006710742,0.00024745005,0.00058259396,0.0033098515,0.000017863002,0.0004970216],"genre_scores_gemma":[0.43459886,0.0000644303,0.5652343,0.00001666715,0.000012281625,0.000022044913,0.000008877368,0.000015887728,0.000026653837],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972958,0.00010369861,0.0012600151,0.0003856679,0.0005666931,0.0003881449],"domain_scores_gemma":[0.9888811,0.008868505,0.00058602437,0.0011975116,0.0003666792,0.0001001863],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0015436444,0.00025841096,0.0008323975,0.00016005572,0.000060776798,0.000023822828,0.0012534177,0.00012776046,0.000044093387],"category_scores_gemma":[0.018570477,0.00014317546,0.00009902198,0.0004320906,0.00076729385,0.0003130983,0.0004065297,0.00013242346,0.0000032901771],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004720694,0.000427586,0.00019795362,0.0010134816,0.00006528651,0.000002902056,0.00006931285,0.000020183785,0.00014276971,0.9796642,0.000970319,0.01737882],"study_design_scores_gemma":[0.0004386147,0.00012306531,0.0010565309,0.0009864641,0.00008419619,0.000005827052,0.000036266145,0.047569484,0.0006904324,0.94874763,0.00006727121,0.00019420679],"about_ca_topic_score_codex":0.00004885463,"about_ca_topic_score_gemma":0.00013333607,"teacher_disagreement_score":0.4185097,"about_ca_system_score_codex":0.000028804527,"about_ca_system_score_gemma":0.00019497643,"threshold_uncertainty_score":0.9896965},"labels":[],"label_agreement":null},{"id":"W2927149034","doi":"10.1007/s10463-019-00715-5","title":"Space–time inhomogeneous background intensity estimators for semi-parametric space–time self-exciting point process models","year":2019,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Point processes and geometric inequalities","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"China Scholarship Council; National Natural Science Foundation of China","keywords":"Space time; Mathematics; Point process; Estimator; Intensity (physics); Parametric statistics; Point (geometry); Space (punctuation); Process (computing); Spacetime; Mathematical analysis; Applied mathematics; Statistical physics; Mathematical optimization; Statistics; Geometry; Computer science; Physics; Optics","score_opus":0.08497194484210498,"score_gpt":0.34463566012144076,"score_spread":0.2596637152793358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2927149034","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7359181,0.00011371837,0.2561556,0.00066021824,0.00030911856,0.0016742194,0.0006890906,0.00013779037,0.0043421444],"genre_scores_gemma":[0.7173916,0.000027354605,0.2813878,0.00012368,0.000063451174,0.00003635467,0.00002176011,0.00007913397,0.0008688212],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99645424,0.00005576244,0.001475748,0.00043289215,0.0009292847,0.0006520474],"domain_scores_gemma":[0.99325454,0.0031147297,0.0012111824,0.00084117986,0.0013993474,0.00017902488],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0015032423,0.00047681146,0.0014404941,0.0003655822,0.00015803693,0.00007340671,0.00077964633,0.00022575,0.00011090389],"category_scores_gemma":[0.0062813987,0.00035458608,0.00034306807,0.0011150469,0.00035294905,0.00046080284,0.00031479733,0.000274054,0.000058870486],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017291313,0.001350278,0.000043725504,0.015415833,0.0005967903,0.000009522617,0.0020116346,0.0044149384,0.00039778274,0.97072,0.0044870586,0.00037955685],"study_design_scores_gemma":[0.0005121426,0.0002830866,0.000009081467,0.00083320984,0.00022918194,0.0000661007,0.00047456805,0.18236992,0.008199425,0.80651337,0.00010613904,0.00040376707],"about_ca_topic_score_codex":0.000034625373,"about_ca_topic_score_gemma":0.0000024394506,"teacher_disagreement_score":0.17795497,"about_ca_system_score_codex":0.000056225388,"about_ca_system_score_gemma":0.00027587972,"threshold_uncertainty_score":0.9998906},"labels":[],"label_agreement":null},{"id":"W3009393055","doi":"10.1007/s10463-022-00828-4","title":"On the rate of convergence of image classifiers based on convolutional neural networks","year":2022,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Convolutional neural network; Pattern recognition (psychology); Curse of dimensionality; Artificial intelligence; Rate of convergence; Convergence (economics); Artificial neural network; Dimension (graph theory); Image (mathematics); Contextual image classification; Computer science; Mathematics; Algorithm; Machine learning","score_opus":0.048064738232478206,"score_gpt":0.2954215988966239,"score_spread":0.2473568606641457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3009393055","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014329356,0.000006011903,0.9816763,0.0027503653,0.00012002128,0.00024048536,0.00017019462,0.0000143201305,0.0006929567],"genre_scores_gemma":[0.96420926,0.000004399226,0.035242643,0.00047668492,0.000005394959,0.000028654807,0.000002353686,0.0000044056947,0.000026208263],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99891615,0.00008630401,0.0004418192,0.00012155356,0.00032861836,0.000105561056],"domain_scores_gemma":[0.9980331,0.0007913526,0.0004577276,0.00052658055,0.00016217813,0.00002905943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004878993,0.000085340595,0.00019697058,0.000042991065,0.00013395051,0.000006331554,0.000816344,0.000023431943,0.00006845327],"category_scores_gemma":[0.00025440764,0.000055310404,0.00010020766,0.00032344286,0.00055895303,0.000049975566,0.0001931284,0.00015374506,7.716528e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001700633,0.00020009417,0.0000052147575,0.000044270026,0.000012418726,4.3308717e-7,0.00003446641,0.022664886,0.0007127192,0.97314,0.0028684007,0.0003001069],"study_design_scores_gemma":[0.000082465,0.0002355357,0.00027886545,0.000038095088,0.000009411996,0.0000015128179,0.00002123407,0.8295255,0.012623456,0.15694852,0.0001796256,0.000055772605],"about_ca_topic_score_codex":0.000020523325,"about_ca_topic_score_gemma":6.585861e-7,"teacher_disagreement_score":0.9498799,"about_ca_system_score_codex":0.000010054061,"about_ca_system_score_gemma":0.0000687349,"threshold_uncertainty_score":0.22554927},"labels":[],"label_agreement":null},{"id":"W3033957979","doi":"10.1007/s10463-020-00755-2","title":"Semiparametric methods for left-truncated and right-censored survival data with covariate measurement error","year":2020,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Covariate; Estimator; Truncation (statistics); Statistics; Inference; Mathematics; Nonparametric statistics; Robustness (evolution); Survival analysis; Censoring (clinical trials); Proportional hazards model; Econometrics; Survival function; Observational error; Computer science; Artificial intelligence","score_opus":0.47061113485342626,"score_gpt":0.47446317102927643,"score_spread":0.003852036175850171,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3033957979","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0028891952,0.000079611505,0.99247634,0.00161388,0.0001471375,0.00083782524,0.0014144568,0.000031820866,0.0005097557],"genre_scores_gemma":[0.057924725,0.000024529983,0.9417745,0.00016767459,0.000031309137,0.0000129433565,0.000016970336,0.00003459859,0.000012730731],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972684,0.0002684095,0.0010218216,0.00041941061,0.0006956737,0.0003263354],"domain_scores_gemma":[0.9924459,0.005018038,0.0006238349,0.0008878787,0.00080273824,0.00022159444],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0026604095,0.00029623474,0.0009943843,0.00005940309,0.00010939004,0.000035406738,0.0008482336,0.00010174959,0.00005486705],"category_scores_gemma":[0.03747259,0.00017937219,0.00007176491,0.00037668404,0.00067952054,0.000120334815,0.0003857747,0.00019592718,0.0000014423188],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002044675,0.0003231023,0.000036746856,0.0026397954,0.00034335494,0.000002631616,0.0003799306,0.000018135157,0.0013585074,0.9864305,0.0016312471,0.0066315755],"study_design_scores_gemma":[0.0009595687,0.00054313836,0.00038948827,0.000446878,0.0005597041,0.0000108142,0.00011518495,0.067420356,0.009673297,0.91819274,0.0013494091,0.00033944397],"about_ca_topic_score_codex":0.00002748829,"about_ca_topic_score_gemma":0.000011634424,"teacher_disagreement_score":0.06823778,"about_ca_system_score_codex":0.000012658382,"about_ca_system_score_gemma":0.00017588914,"threshold_uncertainty_score":0.9706352},"labels":[],"label_agreement":null},{"id":"W3038755401","doi":"10.1007/s10463-020-00759-y","title":"Model averaging for linear models with responses missing at random","year":2020,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Mathematics; Monte Carlo method; Linear model; Applied mathematics; Linear regression; Missing data; Sample (material); Statistics; Mean squared error; Sample size determination; Algorithm","score_opus":0.36226702751769685,"score_gpt":0.4239633447612494,"score_spread":0.06169631724355257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3038755401","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018136485,0.000027590906,0.97718924,0.0021688002,0.000046025638,0.00056700734,0.0007128753,0.000030058327,0.0011218865],"genre_scores_gemma":[0.20498279,0.000011265797,0.7944927,0.0003529065,0.000026479014,0.000017905037,0.0000032989535,0.00003104637,0.00008159768],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980691,0.00008264637,0.0008370131,0.00024347081,0.00048331768,0.0002844605],"domain_scores_gemma":[0.9940893,0.0044846125,0.0004577407,0.0003970009,0.00040130806,0.00017003415],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00065279426,0.0002357366,0.00075211824,0.000036055255,0.00014529038,0.000017536215,0.0003935487,0.00007602884,0.00002293206],"category_scores_gemma":[0.010247786,0.00014645685,0.00014086654,0.0001590281,0.0005186361,0.0001107436,0.00016694787,0.00014197372,0.0000015643309],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089588977,0.00016055438,0.0000064134783,0.0019434184,0.00009763802,0.0000031899208,0.0011524132,0.0061154165,0.0013520421,0.985668,0.0012767647,0.0013282809],"study_design_scores_gemma":[0.0005360699,0.000115302304,0.0000027730764,0.00028953585,0.000085985266,0.000003606183,0.00003023621,0.4612349,0.006101846,0.5314392,0.000051933774,0.00010861195],"about_ca_topic_score_codex":0.000005381374,"about_ca_topic_score_gemma":0.0000024055075,"teacher_disagreement_score":0.45511946,"about_ca_system_score_codex":0.000013152073,"about_ca_system_score_gemma":0.00014934069,"threshold_uncertainty_score":0.9980893},"labels":[],"label_agreement":null},{"id":"W3093091831","doi":"10.1007/s10463-020-00766-z","title":"High-dimensional sign-constrained feature selection and grouping","year":2020,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Coordinate descent; Mathematics; Feature selection; Convex optimization; Bounded function; Feature (linguistics); Oracle; Estimator; Mathematical optimization; Regular polygon; Sign (mathematics); Pattern recognition (psychology); Algorithm; Artificial intelligence; Applied mathematics; Computer science; Statistics","score_opus":0.04443399232188285,"score_gpt":0.27983773584236327,"score_spread":0.2354037435204804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093091831","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.107190855,0.00003564626,0.8810029,0.011134974,0.00016159807,0.00016942865,0.000053823707,0.000035190635,0.0002155822],"genre_scores_gemma":[0.6718935,0.000007913222,0.32751417,0.00054862583,0.000019142863,0.0000017697546,0.0000027677377,0.000003267469,0.000008842356],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992491,0.000025109302,0.00023634324,0.00013853777,0.00024722214,0.000103698956],"domain_scores_gemma":[0.9993845,0.00014616834,0.00015309456,0.00011971142,0.00012339534,0.00007313029],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001214054,0.00008774523,0.00019478909,0.000024236815,0.000068965244,0.000022410984,0.00022745148,0.000049769995,0.000011088038],"category_scores_gemma":[0.0003706057,0.000059895596,0.00003787738,0.0001737977,0.0001390735,0.00020626503,0.00014672519,0.00010229356,0.000003874847],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025378322,0.00014697853,0.000021180036,0.000555345,0.000058483634,0.000005283127,0.000679507,0.0007642224,0.029596467,0.94342244,0.008349657,0.01637505],"study_design_scores_gemma":[0.000829656,0.0004590358,0.0012333718,0.0008828302,0.00006360514,0.000057889516,0.00008672053,0.33101407,0.1632507,0.5011222,0.0006128548,0.0003870684],"about_ca_topic_score_codex":0.000009801015,"about_ca_topic_score_gemma":0.0000015758282,"teacher_disagreement_score":0.56470263,"about_ca_system_score_codex":0.0000023215648,"about_ca_system_score_gemma":0.000039378257,"threshold_uncertainty_score":0.24424715},"labels":[],"label_agreement":null},{"id":"W3119150148","doi":"10.1007/s10463-020-00782-z","title":"Efficient likelihood-based inference for the generalized Pareto distribution","year":2021,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Inference; Generalized Pareto distribution; Range (aeronautics); Pareto principle; Applied mathematics; Estimation theory; Pareto distribution; Confidence interval; Statistical inference; Interval estimation; Pareto interpolation; Mathematical optimization; Statistics; Extreme value theory; Computer science; Artificial intelligence","score_opus":0.15754092920924082,"score_gpt":0.41809295406640906,"score_spread":0.2605520248571682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3119150148","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025452638,0.000089320165,0.9694801,0.0016917371,0.00034630598,0.0005246337,0.0021280232,0.000019712652,0.00026754374],"genre_scores_gemma":[0.4231587,0.000018746263,0.5764453,0.0002027607,0.000037049547,0.000057927115,0.00002926626,0.00001731697,0.000032909822],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978447,0.00013679563,0.0009204378,0.00022454269,0.00054460653,0.0003289415],"domain_scores_gemma":[0.9883835,0.009342886,0.00046757894,0.0007523153,0.0009568879,0.00009687815],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0009995288,0.00021406365,0.00055827777,0.00002095677,0.00018293216,0.00003304123,0.0004802844,0.00009344284,0.00007904706],"category_scores_gemma":[0.028527636,0.000121961806,0.00022130577,0.00029587993,0.0006481866,0.000022949333,0.00015110378,0.0001571838,0.0000028374213],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033641547,0.0004416868,0.000023709688,0.0008463824,0.00007457963,0.0000020107457,0.00009422066,0.00080471917,0.0005576603,0.9912532,0.0021020027,0.003766188],"study_design_scores_gemma":[0.00040933883,0.00008734425,0.00039414346,0.00036887737,0.0001898026,0.0000032833734,0.00006484859,0.12207229,0.022835067,0.85252017,0.0008963185,0.0001585469],"about_ca_topic_score_codex":0.000023533272,"about_ca_topic_score_gemma":0.000017747643,"teacher_disagreement_score":0.3977061,"about_ca_system_score_codex":0.000018496165,"about_ca_system_score_gemma":0.00031876954,"threshold_uncertainty_score":0.9796555},"labels":[],"label_agreement":null},{"id":"W3141775592","doi":"10.1007/s10463-021-00793-4","title":"Empirical likelihood meta-analysis with publication bias correction under Copas-like selection model","year":2021,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Restricted maximum likelihood; Statistics; Mathematics; Likelihood principle; Marginal likelihood; Empirical likelihood; Estimator; Likelihood function; Maximum likelihood sequence estimation; Likelihood-ratio test; Maximum likelihood; Inference; Conditional probability distribution; Econometrics; Model selection; Parametric statistics; Selection (genetic algorithm); Quasi-maximum likelihood; Computer science; Artificial intelligence","score_opus":0.3490179428316027,"score_gpt":0.4380967730010622,"score_spread":0.0890788301694595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3141775592","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024614795,0.000036664387,0.9928814,0.0019158948,0.00013150259,0.00026644918,0.0002796255,0.000040166447,0.0019867716],"genre_scores_gemma":[0.18041095,0.0000144545365,0.81872517,0.00039840827,0.000018092796,0.000033661865,0.000025853904,0.000025318051,0.00034808755],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970475,0.00026941436,0.0011428854,0.00037353992,0.00085914833,0.00030752437],"domain_scores_gemma":[0.99434763,0.0023075305,0.00079478347,0.00069900317,0.0017059795,0.00014507581],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009827773,0.00028520875,0.0012935976,0.00015857354,0.00013848404,0.00006595,0.00030955827,0.00014440727,0.0003288254],"category_scores_gemma":[0.005226237,0.00017613055,0.0005332385,0.00153865,0.00041261772,0.00019441881,0.00011520113,0.00026798766,0.0000054809684],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039819584,0.0009492113,0.00012583505,0.00037328337,0.013706973,0.000002989469,0.00021800856,0.0014347442,0.00019976773,0.97592854,0.006215811,0.0008049997],"study_design_scores_gemma":[0.0001670272,0.00010433568,0.000389505,0.000040157018,0.029924238,0.000024442063,0.00008096955,0.10075815,0.005468,0.8627541,0.00007585403,0.00021322997],"about_ca_topic_score_codex":0.000037295118,"about_ca_topic_score_gemma":0.00015243546,"teacher_disagreement_score":0.17794947,"about_ca_system_score_codex":0.000029697389,"about_ca_system_score_gemma":0.00036502845,"threshold_uncertainty_score":0.71823955},"labels":[],"label_agreement":null},{"id":"W3183973360","doi":"10.1007/s10463-021-00804-4","title":"Semiparametric inference on general functionals of two semicontinuous populations","year":2021,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Public Health Ontario; University of Waterloo","funders":"","keywords":"Estimator; Mathematics; Inference; Asymptotic distribution; Applied mathematics; Nonparametric statistics; Context (archaeology); Empirical likelihood; Semiparametric regression; Statistical inference; Semiparametric model; Population; Econometrics; Statistics; Computer science; Artificial intelligence","score_opus":0.2757588511490457,"score_gpt":0.45977002088446434,"score_spread":0.18401116973541864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183973360","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30825573,0.00006804708,0.68237877,0.0003863434,0.00049221335,0.00028488183,0.0009584997,0.000021516247,0.007153988],"genre_scores_gemma":[0.44576642,0.000019785475,0.553854,0.000095361785,0.000030078825,0.0000074063787,0.000009353052,0.000014204315,0.00020342403],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99744207,0.00015802958,0.001235408,0.00022903888,0.0006930514,0.00024237708],"domain_scores_gemma":[0.993365,0.0042359205,0.00070714473,0.0006938151,0.0008989034,0.000099254234],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00060293626,0.00021314346,0.000759462,0.0001150171,0.00007118602,0.000015176384,0.00035410022,0.000093357754,0.00025602797],"category_scores_gemma":[0.025430229,0.00015402806,0.00018448789,0.0006421717,0.0004896269,0.00006881237,0.00017071326,0.00021092153,0.000006416879],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000160088,0.0006670239,0.00034924748,0.0005334314,0.00007906156,0.0000042185657,0.00010245354,0.00032708817,0.0021277026,0.9910655,0.0013626766,0.0033655942],"study_design_scores_gemma":[0.00027101496,0.0001246906,0.0021804767,0.00049848796,0.000112143345,0.000010603259,0.000036277757,0.0033171673,0.030405369,0.962782,0.00011015515,0.0001515905],"about_ca_topic_score_codex":0.000049535105,"about_ca_topic_score_gemma":0.000015224174,"teacher_disagreement_score":0.13751067,"about_ca_system_score_codex":0.000014204844,"about_ca_system_score_gemma":0.00020402903,"threshold_uncertainty_score":0.98277897},"labels":[],"label_agreement":null},{"id":"W3199271261","doi":"10.1007/s10463-022-00841-7","title":"Group least squares regression for linear models with strongly correlated predictor variables","year":2022,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Multicollinearity; Statistics; Linear regression; Partial least squares regression; Mathematics; Ordinary least squares; Regression analysis; Regression; Least-squares function approximation; Regression diagnostic; Generalized least squares; Total least squares; Simple linear regression; Variables; Econometrics; Robust regression; Bayesian multivariate linear regression","score_opus":0.1606818210749501,"score_gpt":0.401959249251053,"score_spread":0.24127742817610287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199271261","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013280475,0.000049441882,0.9814495,0.0002077765,0.00023007758,0.00096237,0.0032082358,0.00004280088,0.0005693336],"genre_scores_gemma":[0.2027498,0.000011039435,0.7967577,0.000039465922,0.00002895065,0.00012270526,0.000036976864,0.00004770272,0.00020563837],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997506,0.00013836497,0.00092251675,0.00030227596,0.0007729653,0.00035782636],"domain_scores_gemma":[0.9957419,0.0024700104,0.00071367796,0.00059553905,0.00035688962,0.000121985206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081621046,0.00028096707,0.0007394958,0.000069534006,0.0003100081,0.000011597604,0.00052944996,0.00007820003,0.000060447543],"category_scores_gemma":[0.0018290135,0.0001758342,0.0001385615,0.00023522066,0.00049689197,0.00017199396,0.00029598398,0.0002948263,4.0382506e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040857404,0.0007539777,0.00000796394,0.0011315731,0.00013380511,0.000004456335,0.00043097572,0.018213844,0.00025413404,0.9766616,0.0010987305,0.0009003377],"study_design_scores_gemma":[0.00068343134,0.0006256903,0.000009304017,0.00040573874,0.00016589163,0.000013763591,0.00024213409,0.18325943,0.0004922128,0.8135054,0.0004169891,0.00017998529],"about_ca_topic_score_codex":0.000018423207,"about_ca_topic_score_gemma":0.000005774309,"teacher_disagreement_score":0.18946932,"about_ca_system_score_codex":0.000027667977,"about_ca_system_score_gemma":0.00011818112,"threshold_uncertainty_score":0.71703106},"labels":[],"label_agreement":null},{"id":"W4230320142","doi":"10.1007/s10463-009-0239-z","title":"Semiparametric marginal and association regression methods for clustered binary data","year":2009,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; University of Waterloo","funders":"National Heart, Lung, and Blood Institute; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Science Foundation","keywords":"Inference; Semiparametric regression; Nuisance parameter; Marginal model; Mathematics; Econometrics; Binary data; Statistics; Association (psychology); Binary number; Semiparametric model; Regression; Statistical inference; Regression analysis; Computer science; Artificial intelligence; Estimator; Psychology","score_opus":0.13702687448004242,"score_gpt":0.4420097317015558,"score_spread":0.30498285722151336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230320142","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00079700886,0.00024557445,0.99492216,0.003109272,0.00019590865,0.00026798795,0.00009823657,0.000014234131,0.00034962548],"genre_scores_gemma":[0.01395196,0.00008470734,0.98558563,0.00025157514,0.000020966963,0.0000027213055,0.0000073224974,0.000004670449,0.000090462614],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99874616,0.000142585,0.00044393257,0.00023384599,0.0002572622,0.00017620352],"domain_scores_gemma":[0.99720746,0.00128288,0.00044778094,0.00081436185,0.00018397272,0.00006356992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002232596,0.00011896316,0.00035691762,0.00007831089,0.00007696337,0.000036987083,0.0009684593,0.00008984838,0.0000013303517],"category_scores_gemma":[0.003337573,0.000076424694,0.00005175614,0.0003018576,0.000082891536,0.0003198158,0.00036676147,0.000101336744,3.035759e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014938611,0.00015668079,0.000008019878,0.00022678838,0.000031247597,7.9720917e-7,0.00015346914,0.000010277444,0.0009881224,0.6902609,0.004625568,0.30352318],"study_design_scores_gemma":[0.00021074968,0.00014821933,0.0005134419,0.00018509157,0.000041744068,0.000006711592,0.0000040615514,0.21614265,0.0028231982,0.7786434,0.0011829959,0.000097711614],"about_ca_topic_score_codex":0.0000037876991,"about_ca_topic_score_gemma":4.5352226e-7,"teacher_disagreement_score":0.3034255,"about_ca_system_score_codex":0.000010856771,"about_ca_system_score_gemma":0.000058087157,"threshold_uncertainty_score":0.39956278},"labels":[],"label_agreement":null},{"id":"W4281387922","doi":"10.1007/s10463-022-00835-5","title":"Semiparametric modelling of two-component mixtures with stochastic dominance","year":2022,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Mathematics; Estimator; Semiparametric regression; Statistics; Applied mathematics; Asymptotic distribution; Monte Carlo method; Econometrics","score_opus":0.06664828147712305,"score_gpt":0.31125365926413384,"score_spread":0.2446053777870108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281387922","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01796181,0.00019511832,0.9806617,0.0002373618,0.00016806778,0.00025692608,0.00008829563,0.000012373814,0.00041836538],"genre_scores_gemma":[0.47981855,0.000005080268,0.5200944,0.00004323922,0.0000056253316,0.000009060177,7.672148e-7,0.00000598143,0.000017272176],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981889,0.00010200893,0.0005924167,0.0002190304,0.0006871198,0.0002105321],"domain_scores_gemma":[0.9979492,0.0005561328,0.00054968026,0.00069947884,0.00018416539,0.000061345054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007150962,0.00015626599,0.0004887367,0.00012234178,0.00011369357,0.000013338491,0.0011273194,0.000026665119,0.000008759255],"category_scores_gemma":[0.00017944661,0.00010445099,0.00009804089,0.0006399078,0.00031357957,0.00012220241,0.00044187187,0.00019626631,4.3163521e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024115341,0.00028088992,0.0000016297909,0.00021444607,0.000042821048,0.0000041096473,0.00049410766,0.21257544,0.00051680394,0.78243136,0.00014321806,0.0032710868],"study_design_scores_gemma":[0.0002530006,0.0001633796,0.000008326003,0.00013753118,0.00003307568,0.000025822741,0.000011075066,0.48769027,0.007115446,0.5044232,0.000026512407,0.00011236266],"about_ca_topic_score_codex":0.000049759525,"about_ca_topic_score_gemma":0.0000012430011,"teacher_disagreement_score":0.46185675,"about_ca_system_score_codex":0.000012228892,"about_ca_system_score_gemma":0.000120006975,"threshold_uncertainty_score":0.42593879},"labels":[],"label_agreement":null},{"id":"W4315648476","doi":"10.1007/s10463-022-00861-3","title":"Correction to: Group least squares regression for linear models with strongly correlated predictor variables","year":2023,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Mathematics; Statistics; Linear regression; Generalized least squares; Regression; Group (periodic table); Total least squares; Regression analysis; Chemistry","score_opus":0.06068453922395285,"score_gpt":0.3102164468924399,"score_spread":0.24953190766848704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4315648476","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0298337,0.000007616394,0.9677575,0.00048393232,0.0008518387,0.00045131566,0.0001886462,0.00008487929,0.0003405241],"genre_scores_gemma":[0.5407193,0.000023838884,0.45854732,0.00008568792,0.000043608903,0.00006307383,0.00005102741,0.000019613937,0.00044655078],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99879175,0.000029302548,0.00038587608,0.0002015303,0.0003903809,0.00020118532],"domain_scores_gemma":[0.99855554,0.00046273845,0.00022829123,0.00036478497,0.00030530535,0.000083319384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028998425,0.00013294819,0.00025559872,0.00009284323,0.000117787225,0.000027454293,0.00044927458,0.000060514572,0.0000048768916],"category_scores_gemma":[0.00048261628,0.00007974312,0.000058599133,0.00043584872,0.00011146981,0.0003288471,0.00016675155,0.00009386068,0.000009517318],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044543383,0.00087551906,0.000096062715,0.0015166028,0.00018174562,0.000008606054,0.0026084543,0.19020808,0.0045874026,0.6741781,0.1114908,0.013803181],"study_design_scores_gemma":[0.0003249594,0.00039810556,0.0002092466,0.0017378405,0.000026770998,0.000005173825,0.00009744179,0.9215879,0.005180164,0.0699445,0.00036465458,0.00012328],"about_ca_topic_score_codex":0.00002971534,"about_ca_topic_score_gemma":0.000009139961,"teacher_disagreement_score":0.7313798,"about_ca_system_score_codex":0.0000075448083,"about_ca_system_score_gemma":0.0000616765,"threshold_uncertainty_score":0.325183},"labels":[],"label_agreement":null},{"id":"W4319945856","doi":"10.1007/s10463-023-00865-7","title":"Mixture of shifted binomial distributions for rating data","year":2023,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Mathematics; Categorical variable; Estimator; Expectation–maximization algorithm; Statistics; Binomial distribution; Binomial (polynomial); Ordinal data; Mixture model; Maximum likelihood; Econometrics; Applied mathematics","score_opus":0.16659196732130865,"score_gpt":0.39384389044840235,"score_spread":0.2272519231270937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319945856","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00362916,0.000023799066,0.99160314,0.0016141245,0.00026491712,0.0002723584,0.0023602517,0.000025416057,0.00020685267],"genre_scores_gemma":[0.102420874,0.000012446574,0.8973867,0.000040647534,0.000028467268,0.0000069902994,0.00006511667,0.0000065182917,0.00003223012],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99875355,0.000045779077,0.00056363805,0.00019219462,0.00026020495,0.00018466514],"domain_scores_gemma":[0.99755263,0.0008014272,0.00033338642,0.0010412661,0.0002197841,0.000051486833],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008887916,0.00010576767,0.0003409331,0.000050977495,0.00008006884,0.000018431665,0.0015069449,0.00006218014,0.0000025488653],"category_scores_gemma":[0.0023939116,0.00007249762,0.0000844263,0.00044260186,0.00025577878,0.0001979775,0.0006344771,0.000082355975,0.0000012964633],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000055604914,0.00008931501,0.000004050279,0.00040807115,0.000038542363,9.2098566e-7,0.00019118874,0.000023790302,0.0011134082,0.98173547,0.0056099603,0.010779703],"study_design_scores_gemma":[0.00016962634,0.000052761796,0.00014734638,0.00018046032,0.000033670607,0.0000025796496,0.000010297324,0.12890013,0.012766473,0.85694027,0.0007098164,0.00008659586],"about_ca_topic_score_codex":0.000012775651,"about_ca_topic_score_gemma":0.000005489302,"teacher_disagreement_score":0.12887634,"about_ca_system_score_codex":0.0000034884797,"about_ca_system_score_gemma":0.000120572724,"threshold_uncertainty_score":0.2956367},"labels":[],"label_agreement":null},{"id":"W4367845396","doi":"10.1007/s10463-023-00870-w","title":"Robust variable selection with exponential squared loss for partially linear spatial autoregressive models","year":2023,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Mathematics; Autoregressive model; Estimator; STAR model; Orthogonality; Model selection; Applied mathematics; Selection (genetic algorithm); Statistics; Feature selection; Exponential function; Mathematical optimization; Computer science; Autoregressive integrated moving average; Artificial intelligence; Time series","score_opus":0.15022352497789485,"score_gpt":0.28477940392332657,"score_spread":0.13455587894543172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367845396","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019777201,0.00002001043,0.9757811,0.00036972368,0.00022371949,0.0003072184,0.0029601157,0.000026000036,0.00053495786],"genre_scores_gemma":[0.82127994,0.000041758583,0.1778498,0.000059431317,0.00015000846,0.000054968958,0.00024119085,0.000030209607,0.0002926974],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986889,0.00001240656,0.0007214975,0.00022713256,0.000117180236,0.0002328806],"domain_scores_gemma":[0.99869186,0.00018323651,0.0005760291,0.00029474573,0.00019415529,0.000059971953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004110254,0.00014228754,0.00050247175,0.00011900321,0.00011251557,0.000023648383,0.00028814332,0.000079865116,0.00008284921],"category_scores_gemma":[0.00048016245,0.00010911987,0.00011528386,0.000360302,0.00020138655,0.00019946143,0.00007265459,0.00007673119,0.000022406832],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010935596,0.00019182064,0.00025710973,0.00038935998,0.00025817778,0.0000026236564,0.0003277243,0.153205,0.00005557567,0.84346235,0.001501834,0.00023905588],"study_design_scores_gemma":[0.0003588577,0.00014504784,0.00036915258,0.00009623464,0.00006634416,0.0000020688396,0.00002659114,0.6345958,0.00083505403,0.3625943,0.0007698281,0.00014067558],"about_ca_topic_score_codex":0.00076262275,"about_ca_topic_score_gemma":0.00015195642,"teacher_disagreement_score":0.80150276,"about_ca_system_score_codex":0.000011072528,"about_ca_system_score_gemma":0.00006027776,"threshold_uncertainty_score":0.4449779},"labels":[],"label_agreement":null},{"id":"W4388498730","doi":"10.1007/s10463-023-00883-5","title":"Multivariate frequency polygon for stationary random fields","year":2023,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Mathematics; Estimator; Rate of convergence; Polygon (computer graphics); Uniform convergence; Convergence (economics); Applied mathematics; Kernel (algebra); Mathematical optimization; Statistics; Combinatorics; Bandwidth (computing); Computer science","score_opus":0.1397300875317433,"score_gpt":0.3305972478181866,"score_spread":0.19086716028644332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388498730","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17075647,0.00015728256,0.8225474,0.0013579279,0.0005135893,0.0004531395,0.0022735556,0.000025242607,0.0019154272],"genre_scores_gemma":[0.92044526,0.00009311492,0.07908442,0.00008314707,0.000036175992,0.000023063518,0.000032478885,0.000013490635,0.00018885994],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99879736,0.000008302883,0.00080293487,0.00014908107,0.00006509014,0.00017724323],"domain_scores_gemma":[0.99876064,0.00047077745,0.00036346167,0.00026394543,0.000105788095,0.000035369307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006347036,0.00009677983,0.0003897896,0.00008872149,0.00008409911,0.000009884311,0.00023273651,0.000074962234,0.00002705593],"category_scores_gemma":[0.0022771943,0.00008281777,0.00013499348,0.00020730535,0.00013248842,0.00011348378,0.000057704885,0.00007379809,0.000024561643],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032577827,0.000089386725,0.0003344075,0.00034996268,0.000036384543,4.975666e-7,0.00053860736,0.0010790373,0.000061310806,0.99552965,0.0011823091,0.00076589285],"study_design_scores_gemma":[0.00043458905,0.00005001423,0.0026304757,0.000071839335,0.000008879303,3.4014033e-7,0.000030687967,0.08680126,0.00035816507,0.90885305,0.0006715047,0.00008918109],"about_ca_topic_score_codex":0.00023456984,"about_ca_topic_score_gemma":0.0000162943,"teacher_disagreement_score":0.7496888,"about_ca_system_score_codex":0.0000071942027,"about_ca_system_score_gemma":0.000036596277,"threshold_uncertainty_score":0.33772108},"labels":[],"label_agreement":null},{"id":"W4390616709","doi":"10.1007/s10463-023-00891-5","title":"Gradual change-point analysis based on Spearman matrices for multivariate time series","year":2024,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Mathematics; Multivariate statistics; Estimator; Series (stratigraphy); Statistics; Context (archaeology); Multivariate t-distribution; Sequence (biology); Multivariate analysis; Econometrics; Applied mathematics; Multivariate normal distribution; Geography","score_opus":0.20505833550082084,"score_gpt":0.43243888396681934,"score_spread":0.2273805484659985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390616709","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0032011839,0.00005238293,0.99022424,0.001691355,0.00029857078,0.00071321573,0.002262913,0.0000665779,0.0014895553],"genre_scores_gemma":[0.13033798,0.000017383878,0.869124,0.0001494597,0.00008420637,0.0000639576,0.000022747921,0.00003681025,0.00016344246],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979379,0.0000877572,0.00086843135,0.0002851677,0.0005267889,0.00029395605],"domain_scores_gemma":[0.9939557,0.0048309644,0.00030594016,0.00053455995,0.0002698747,0.00010296979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010598414,0.00026520976,0.0007852198,0.00023477535,0.00008781213,0.000055852393,0.0003981532,0.000093481096,0.00019282925],"category_scores_gemma":[0.0049932906,0.00016931229,0.00035317757,0.0006856306,0.00042623063,0.00013533872,0.00009416208,0.00015559478,0.000018323974],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007016351,0.0003389888,0.0000067656547,0.002433314,0.0004648685,0.000006629028,0.00036145383,0.000096456715,0.00021439254,0.98993725,0.0023926245,0.003677093],"study_design_scores_gemma":[0.00015930468,0.00029498158,0.00016854412,0.00066507177,0.00088719896,0.0000021943729,0.000031543164,0.17924622,0.0032521873,0.81457776,0.0005236667,0.00019133529],"about_ca_topic_score_codex":0.00003675852,"about_ca_topic_score_gemma":0.0000073326873,"teacher_disagreement_score":0.17914976,"about_ca_system_score_codex":0.000015562242,"about_ca_system_score_gemma":0.000073081785,"threshold_uncertainty_score":0.6904355},"labels":[],"label_agreement":null},{"id":"W4395043963","doi":"10.1007/s10463-024-00904-x","title":"Assessing the coverage probabilities of fixed-margin confidence intervals for the tail conditional allocation","year":2024,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Resampling; Margin (machine learning); Confidence interval; Coverage probability; Econometrics; Mathematics; Conditional probability; Statistics; Computer science; Machine learning","score_opus":0.20062472180127758,"score_gpt":0.4594255929366521,"score_spread":0.25880087113537453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395043963","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015826194,0.00028858488,0.97612214,0.004999693,0.00046764995,0.0005885291,0.00054529746,0.000009132337,0.0011527973],"genre_scores_gemma":[0.97953856,0.00015726037,0.019717457,0.00013911632,0.0000403029,0.000033420692,0.000015238384,0.000007982984,0.00035066807],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976404,0.000108614186,0.0010450024,0.00016146417,0.0009221178,0.00012242924],"domain_scores_gemma":[0.9884783,0.009673558,0.00051795016,0.00047573808,0.0008284865,0.000025938582],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003183249,0.00010952988,0.00028745376,0.00006154184,0.00015112385,0.00019782314,0.000729326,0.000047198173,0.000088613146],"category_scores_gemma":[0.009581611,0.000048043974,0.0001570895,0.00033629933,0.0010588797,0.00043325886,0.000105010615,0.00009557479,0.000005471983],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010852663,0.00006563154,0.000038211543,0.00023260766,0.00005976406,3.7088319e-7,0.0010098898,0.012385358,0.00016506095,0.9700522,0.009087572,0.006892509],"study_design_scores_gemma":[0.00007036846,0.00004979328,0.00076879596,0.00031463752,0.000059311045,0.0000050119615,0.00067787955,0.10131498,0.0031527001,0.88924444,0.00428223,0.0000598379],"about_ca_topic_score_codex":0.000030515084,"about_ca_topic_score_gemma":0.00001271535,"teacher_disagreement_score":0.96371233,"about_ca_system_score_codex":0.000008647874,"about_ca_system_score_gemma":0.0002378827,"threshold_uncertainty_score":0.9987611},"labels":[],"label_agreement":null},{"id":"W4402782255","doi":"10.1007/s10463-024-00909-6","title":"Improved confidence intervals for nonlinear mixed-effects and nonparametric regression models","year":2024,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Mathematics; Statistics; Confidence interval; Nonparametric statistics; CDF-based nonparametric confidence interval; Nonparametric regression; Robust confidence intervals; Mixed model; Nonlinear regression; Econometrics; Regression analysis","score_opus":0.16175404278736677,"score_gpt":0.4517508378405108,"score_spread":0.289996795053144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402782255","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005992957,0.0005203645,0.99073446,0.000314665,0.00046293472,0.00089340436,0.00074478413,0.000041443902,0.00029501755],"genre_scores_gemma":[0.15604553,0.00013643347,0.8435114,0.000056724883,0.00003624529,0.000047858855,0.0000049034616,0.000035403948,0.0001255171],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981002,0.000075678625,0.00087590015,0.0003197036,0.00034091726,0.00028756735],"domain_scores_gemma":[0.99054646,0.008271865,0.00029976893,0.0004472182,0.00030682798,0.000127878],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0009050717,0.00026083144,0.00073804543,0.000111727764,0.000078656594,0.000038812184,0.00031960726,0.00012293046,0.0000058634582],"category_scores_gemma":[0.009959578,0.00016059888,0.00016730891,0.00026008507,0.00056963763,0.00022638474,0.00019867609,0.00019588423,8.4826985e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038485934,0.00017609494,3.593226e-7,0.007966191,0.000091284244,0.000004403002,0.00025856454,0.00005807871,0.0015218488,0.96573895,0.0008901192,0.0232556],"study_design_scores_gemma":[0.00016708292,0.00017841555,0.0000025480806,0.0016340214,0.00012035875,0.000008973827,0.000026330623,0.2828027,0.011961337,0.7028286,0.00014399871,0.00012562865],"about_ca_topic_score_codex":0.000009943548,"about_ca_topic_score_gemma":0.0000032665587,"teacher_disagreement_score":0.28274462,"about_ca_system_score_codex":0.000012426452,"about_ca_system_score_gemma":0.00007212995,"threshold_uncertainty_score":0.99837995},"labels":[],"label_agreement":null},{"id":"W4409898449","doi":"10.1007/s10463-025-00931-2","title":"The family of multivariate beta copulas revisited","year":2025,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; Université Laval","funders":"","keywords":"Mathematics; Multivariate statistics; BETA (programming language); Statistics; Copula (linguistics); Econometrics; Multivariate analysis; Pure mathematics","score_opus":0.08796301573115285,"score_gpt":0.3201863831448856,"score_spread":0.23222336741373278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409898449","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31707445,0.003836022,0.6496727,0.0020304269,0.0007857541,0.0007197244,0.0014765154,0.000018883587,0.024385506],"genre_scores_gemma":[0.9785712,0.00042606314,0.020638414,0.00009302441,0.000012344217,0.0000044975523,0.0000037644027,0.000008003974,0.0002427409],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983838,0.000017501197,0.0012199036,0.00014228527,0.00007804379,0.00015845083],"domain_scores_gemma":[0.99829584,0.00043737487,0.0006305659,0.0004403619,0.00017043123,0.000025450554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008476891,0.0001090554,0.00051926787,0.000065484426,0.00011218379,0.000014137489,0.00045067506,0.00006886476,0.0000071865443],"category_scores_gemma":[0.002043846,0.00007603543,0.00014233652,0.00027710138,0.00039136625,0.00006768071,0.00014351807,0.000114476024,0.0000060592342],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000192555,0.00010799481,0.0006990708,0.00036668446,0.000062418,1.9016807e-7,0.00014503211,0.00015955395,0.00007516195,0.99650204,0.0008243884,0.0010382283],"study_design_scores_gemma":[0.00023166621,0.00003903387,0.01383294,0.0003895765,0.00002693949,2.2895081e-7,0.000041378025,0.036331188,0.0011437949,0.9393302,0.008536993,0.000096041986],"about_ca_topic_score_codex":0.00029952463,"about_ca_topic_score_gemma":0.000019473824,"teacher_disagreement_score":0.6614967,"about_ca_system_score_codex":0.000009500434,"about_ca_system_score_gemma":0.000050112318,"threshold_uncertainty_score":0.3100635},"labels":[],"label_agreement":null},{"id":"W4413331342","doi":"10.1007/s10463-025-00952-x","title":"Asymptotic normality of multivariate frequency polygons for stationary random fields","year":2025,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Mathematics; Multivariate statistics; Asymptotic distribution; Normality; Statistics; Local asymptotic normality; Multivariate analysis; Multivariate normal distribution; Applied mathematics; Estimator","score_opus":0.07786156626775866,"score_gpt":0.32277670778193,"score_spread":0.24491514151417138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413331342","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11942727,0.00025397984,0.8741292,0.0006837026,0.00030839487,0.00037583525,0.001546715,0.000005854233,0.0032690528],"genre_scores_gemma":[0.8962188,0.000048171405,0.103506155,0.0000751076,0.000010789318,0.0000124687695,0.000011969876,0.0000058284113,0.00011070626],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985165,0.000013195256,0.0011268464,0.00014111001,0.00005845217,0.00014391939],"domain_scores_gemma":[0.9983547,0.00059986976,0.00051832956,0.00031447667,0.00018612247,0.000026543847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006437728,0.000101449885,0.00052679295,0.00008668022,0.00006686478,0.0000065131812,0.00026205936,0.00008304918,0.000019516248],"category_scores_gemma":[0.0026961765,0.00008828639,0.00016292663,0.0001661393,0.00021920189,0.00010616105,0.000064385444,0.00008122638,0.0000016997853],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005204791,0.00022501548,0.0011870537,0.0008527753,0.00007108491,1.2837714e-7,0.00029839145,0.0008769879,0.000053644515,0.99566734,0.00020671195,0.0005088384],"study_design_scores_gemma":[0.00059449696,0.000052603784,0.006108438,0.00018106408,0.000025617086,2.0444747e-7,0.00002322274,0.044390727,0.0010115849,0.9472908,0.00024116856,0.000080122176],"about_ca_topic_score_codex":0.000439927,"about_ca_topic_score_gemma":0.000034166846,"teacher_disagreement_score":0.7767915,"about_ca_system_score_codex":0.000010031424,"about_ca_system_score_gemma":0.0000822767,"threshold_uncertainty_score":0.36002144},"labels":[],"label_agreement":null}]}