{"meta":{"query_hash":"55ce858ebb80","filters":{"venue":"Statistical Papers"},"cohort_total":84,"direct_labels_cover":0,"predictions_cover":84,"exported":84,"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/55ce858ebb80","api":"https://metacan.xera.ac/api/v1/cohort?venue=Statistical+Papers"},"results":[{"id":"W1578220446","doi":"10.1007/s00362-007-0099-7","title":"Robert E. Weiss (2006): Modeling longitudinal data","year":2008,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Advanced Causal Inference Techniques","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 Manitoba","funders":"","keywords":"Longitudinal data; Sociology; Demography","score_opus":0.292524825356008,"score_gpt":0.4326743019312527,"score_spread":0.14014947657524474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1578220446","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":[0.0030555727,0.000049609378,0.9691717,0.00013878515,0.000073521645,0.00018599481,0.0003497753,0.00043011297,0.026544921],"genre_scores_gemma":[0.5440015,0.00005530779,0.45511293,0.000101476144,0.000067338784,0.000013682577,0.000120675424,0.00003581264,0.00049121835],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983779,0.000047767968,0.00035136673,0.00046677966,0.00034767578,0.00040847718],"domain_scores_gemma":[0.9981427,0.00068537233,0.00005590637,0.0008742464,0.00007188368,0.0001698464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002156749,0.00020269498,0.0002886339,0.000043535998,0.00016231964,0.000017863866,0.0004683645,0.00008687479,0.0007782923],"category_scores_gemma":[0.0018056575,0.00018135253,0.000027751305,0.000113307746,0.00021387616,0.00021263998,0.00025139435,0.00027685356,0.0000780675],"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":[0.000059148988,0.00019576229,0.0008498519,0.00009198417,0.00006298935,0.00039113322,0.00017740871,0.00021862259,0.00077009236,0.95550424,0.03207607,0.009602701],"study_design_scores_gemma":[0.00041673423,0.00015582239,0.0005058134,0.00008013841,0.000085968044,0.00017728067,0.00010093069,0.09340234,0.00018277638,0.8995762,0.0046208957,0.0006951176],"about_ca_topic_score_codex":0.00008251908,"about_ca_topic_score_gemma":0.000058232294,"teacher_disagreement_score":0.54094595,"about_ca_system_score_codex":0.000061382976,"about_ca_system_score_gemma":0.00006772628,"threshold_uncertainty_score":0.8521755},"labels":[],"label_agreement":null},{"id":"W1965075095","doi":"10.1007/s00362-013-0556-4","title":"On tests of radial symmetry for bivariate copulas","year":2013,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Copula (linguistics); Bivariate analysis; Mathematics; Asymptotic distribution; Applied mathematics; Inference; Statistical hypothesis testing; Statistics; Econometrics; Computer science","score_opus":0.0275908102003899,"score_gpt":0.24903266791096162,"score_spread":0.22144185771057173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965075095","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":[0.5661686,0.00041235815,0.34028113,0.00085244305,0.0014853328,0.0015099315,0.0044607255,0.00008043695,0.08474904],"genre_scores_gemma":[0.98304623,0.000013962574,0.0164022,0.00017924471,0.000057745478,0.00003416324,0.000034142344,0.000016337333,0.00021594897],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99902797,0.0000076280853,0.00044205948,0.00025555666,0.00003303987,0.00023377467],"domain_scores_gemma":[0.99910927,0.0005012858,0.00011426624,0.00016190385,0.000031484746,0.000081773265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018526174,0.00010082209,0.00030023992,0.000081345985,0.000057081106,0.00002071314,0.00009668735,0.0000767384,0.0007234916],"category_scores_gemma":[0.0012305842,0.00010682183,0.00006917528,0.00008781164,0.000067770954,0.00005538543,0.000015021132,0.000085258835,0.0003105929],"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":[0.000032461594,0.00005226854,0.00339745,0.000034744397,0.000013055834,3.1625038e-7,0.000051388786,0.00004971039,0.00007817267,0.9898749,0.0017160798,0.004699439],"study_design_scores_gemma":[0.00071439653,0.00031102542,0.08304085,0.000016008513,0.0000068344675,2.3660324e-7,0.000016871276,0.021158934,0.000030369501,0.8911873,0.00331799,0.00019917758],"about_ca_topic_score_codex":0.0005611715,"about_ca_topic_score_gemma":0.00001596217,"teacher_disagreement_score":0.41687766,"about_ca_system_score_codex":0.00003685754,"about_ca_system_score_gemma":0.000015936794,"threshold_uncertainty_score":0.79217255},"labels":[],"label_agreement":null},{"id":"W1966937304","doi":"10.1007/s00362-005-0285-4","title":"Dispersive ordering—Some applications and examples","year":2006,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Quantile; Independent and identically distributed random variables; Order statistic; Mathematics; Poisson distribution; Random variable; Convolution (computer science); Combinatorics; Order (exchange); Statistics; Distribution (mathematics); Homogeneous; Mathematical analysis; Computer science","score_opus":0.029425058387283588,"score_gpt":0.3210744817156525,"score_spread":0.2916494233283689,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966937304","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":[0.0015905019,0.00004353494,0.97035366,0.00070920953,0.000021139736,0.00040752385,0.0012183177,0.0001554141,0.025500666],"genre_scores_gemma":[0.88264215,0.000014559291,0.115494035,0.00022052381,0.00010409808,0.0003408386,0.00044273018,0.000024709188,0.0007163752],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990279,0.000028536388,0.00027214165,0.00027046245,0.00017863148,0.00022230418],"domain_scores_gemma":[0.99841803,0.0011517832,0.0000561794,0.00018222119,0.00005626447,0.00013552928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000071140916,0.00013439724,0.00015951347,0.000032926237,0.00021759167,0.000048469723,0.00007982691,0.00005049127,0.0007408151],"category_scores_gemma":[0.0003583006,0.00012537272,0.000024768759,0.00013026838,0.00030492534,0.000054605443,0.000032840326,0.00009493933,0.00010510562],"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":[0.0000035202565,0.0000748495,0.00007798832,0.00003415822,0.0000074692216,0.0000014969283,0.00001352425,0.0000026250443,0.00044676676,0.9904113,0.0046911663,0.004235145],"study_design_scores_gemma":[0.00029955347,0.000019584879,0.020482926,0.000007686316,0.000046844114,0.000007087679,0.00010845233,0.0008109454,0.00004880048,0.9395103,0.038455553,0.00020229067],"about_ca_topic_score_codex":0.00004863272,"about_ca_topic_score_gemma":0.000022203267,"teacher_disagreement_score":0.8810516,"about_ca_system_score_codex":0.000037506263,"about_ca_system_score_gemma":0.000021632984,"threshold_uncertainty_score":0.8111406},"labels":[],"label_agreement":null},{"id":"W1973607231","doi":"10.1007/bf02762840","title":"Estimation of the intercept parameter for linear regression model with uncertain non-sample prior information","year":2005,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Advanced Statistical Methods and Models","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":"Carleton University","funders":"","keywords":"Estimator; Statistics; Mathematics; Linear regression; Sample (material); Regression analysis; Shrinkage estimator; Mean squared error; Quadratic equation; Linear model; Regression; Value (mathematics); Bias of an estimator; Minimum-variance unbiased estimator","score_opus":0.06505990704481077,"score_gpt":0.4086999005172391,"score_spread":0.34363999347242835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973607231","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":[0.0030430006,0.0000015708919,0.99490666,0.000257482,0.000032643544,0.0006098986,0.0005407838,0.000022972774,0.0005849927],"genre_scores_gemma":[0.2516059,0.0000014076736,0.7480467,0.00014795529,0.000014977143,0.00005790722,0.00003223136,0.000013230111,0.00007970445],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989202,0.00004854657,0.00041098025,0.00015114793,0.0002586195,0.00021049827],"domain_scores_gemma":[0.9961212,0.0032722226,0.0001812835,0.00024359475,0.00010732393,0.000074333926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002388595,0.00014936076,0.00024087258,0.000029603347,0.00010349105,0.000014245688,0.00012322536,0.00006764809,0.000041786945],"category_scores_gemma":[0.0045854673,0.00008292959,0.00005144438,0.00007437212,0.00015719452,0.000193662,0.00003593009,0.00013037551,0.0000025468344],"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":[0.00037667333,0.000080596175,0.000007800214,0.00032123982,0.000025857496,2.0464577e-7,0.0011103972,0.087166265,0.00024180544,0.39366993,0.00075143337,0.5162478],"study_design_scores_gemma":[0.00046942986,0.00011551855,0.00003459619,0.00009263103,0.000044660977,8.520486e-7,0.00008087391,0.7383801,0.00041982904,0.25996354,0.0003000197,0.00009794609],"about_ca_topic_score_codex":0.0000076060574,"about_ca_topic_score_gemma":0.000012827425,"teacher_disagreement_score":0.6512138,"about_ca_system_score_codex":0.00005564162,"about_ca_system_score_gemma":0.000056210683,"threshold_uncertainty_score":0.5489564},"labels":[],"label_agreement":null},{"id":"W1973757433","doi":"10.1007/s00362-002-0102-2","title":"Improved estimators for the selected location parameters","year":2002,"lang":"en","type":"article","venue":"Statistical Papers","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":"University of New Brunswick","funders":"","keywords":"Estimator; Mathematics; Statistics; Mean squared error; Population; Constant (computer programming); Bias of an estimator; Combinatorics; Minimum-variance unbiased estimator; Computer science; Demography","score_opus":0.08180471174314698,"score_gpt":0.35345761122787545,"score_spread":0.2716528994847285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973757433","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":[0.0007143082,0.00003933297,0.9959343,0.00053922745,0.00018119863,0.00056149496,0.00013150138,0.00008839482,0.0018102169],"genre_scores_gemma":[0.29912013,0.000007963033,0.70017296,0.00024599122,0.000035108045,0.00015091275,0.000007866142,0.000024492432,0.00023457159],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882996,0.000093291885,0.00030429152,0.00025283216,0.00017724551,0.00034238442],"domain_scores_gemma":[0.9857105,0.013679001,0.000073529656,0.0002500902,0.00016592021,0.00012097692],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00027969017,0.00015855014,0.00020797094,0.000023138611,0.00019159306,0.000052270887,0.00016361414,0.00006746356,0.00076681614],"category_scores_gemma":[0.019283516,0.00010275584,0.00003937543,0.00023498331,0.00022467035,0.000027152862,0.000018954604,0.00015239722,0.00002970639],"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":[0.00003776046,0.000085405416,0.000047325342,0.00010817458,0.000066647066,0.0000017621384,0.00018226946,0.000011604312,0.00056342775,0.80031884,0.013002521,0.18557428],"study_design_scores_gemma":[0.0007971082,0.00040351273,0.0024532168,0.000033718272,0.0002393204,0.0000070458364,0.00021349387,0.5493912,0.0002947948,0.44346192,0.002316598,0.0003880544],"about_ca_topic_score_codex":0.000029306713,"about_ca_topic_score_gemma":0.000013921599,"teacher_disagreement_score":0.5493796,"about_ca_system_score_codex":0.00003978194,"about_ca_system_score_gemma":0.000022505063,"threshold_uncertainty_score":0.9889775},"labels":[],"label_agreement":null},{"id":"W1974965884","doi":"10.1007/s00362-015-0665-3","title":"Testing homogeneity in a scale mixture of normal distributions","year":2015,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","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":"University of Waterloo; University of Alberta","funders":"","keywords":"Homogeneity (statistics); Mathematics; Normal distribution; Statistics; Statistical physics; Physics","score_opus":0.03019725257155906,"score_gpt":0.2887532781627109,"score_spread":0.2585560255911518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974965884","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":[0.00424096,0.000041170806,0.9763971,0.0002034519,0.000095842704,0.00007197438,0.000093877235,0.00003001095,0.01882563],"genre_scores_gemma":[0.44856715,4.3307878e-7,0.5513472,0.00004269111,0.000013285071,0.0000037136815,0.0000051084066,0.0000024296737,0.000017977633],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99902076,0.00012195427,0.00020874955,0.00022131397,0.00018997958,0.00023723683],"domain_scores_gemma":[0.9991695,0.0002869839,0.000041303938,0.00023337608,0.00008335155,0.00018548232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040611046,0.00008716273,0.00016328157,0.00003779549,0.000033974247,0.000021481974,0.00027832107,0.000054230906,0.000009008495],"category_scores_gemma":[0.0006693351,0.000075951604,0.000023850185,0.00038713668,0.00010179304,0.00009747675,0.000107960914,0.00013875292,0.000005587595],"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":[0.000013738152,0.0001452739,0.008716733,0.000028702641,0.000007806752,0.000050170656,0.0004592945,0.0000377191,0.004253337,0.7811781,0.0009620108,0.20414712],"study_design_scores_gemma":[0.0022293953,0.00061838556,0.32806617,0.00013121805,0.000041917585,0.000096040305,0.00009507238,0.08084495,0.003956009,0.57962024,0.0034020424,0.000898559],"about_ca_topic_score_codex":0.00010347196,"about_ca_topic_score_gemma":0.00004812167,"teacher_disagreement_score":0.4443262,"about_ca_system_score_codex":0.00003672051,"about_ca_system_score_gemma":0.00012889488,"threshold_uncertainty_score":0.30972168},"labels":[],"label_agreement":null},{"id":"W1980327886","doi":"10.1007/s00362-003-0143-1","title":"Higher order moments of order statistics from INID exponential random variables","year":2003,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Stochastic processes and statistical mechanics","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":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Statistics; L-moment; Order statistic; Order (exchange); Mathematics; Exponential function; Random variable; Applied mathematics; Statistical physics; Econometrics; Mathematical analysis; Physics; Economics","score_opus":0.027824047724933,"score_gpt":0.2984860028111003,"score_spread":0.2706619550861673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980327886","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":[0.0007312798,0.000058669666,0.979739,0.000042489755,0.000771181,0.000350427,0.003840886,0.000061993116,0.014404061],"genre_scores_gemma":[0.20576108,0.00002628707,0.7927385,0.00016998095,0.00007838195,0.00005160583,0.00015269569,0.00007661637,0.00094487355],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99711335,0.00019593269,0.00086872285,0.00050562806,0.00074742973,0.00056894426],"domain_scores_gemma":[0.99222904,0.006470645,0.00023385813,0.0003913886,0.00038035715,0.00029470795],"candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003202629,0.00036582944,0.0007420089,0.00006586262,0.00012081983,0.000045466957,0.00023450912,0.00018085292,0.013660408],"category_scores_gemma":[0.011743642,0.00031738693,0.00005274475,0.00033918308,0.00025189223,0.00006244048,0.000065822576,0.00026799322,0.000080620346],"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":[0.00026107611,0.00032028553,0.00003107645,0.00016363544,0.00019810609,0.000036616428,0.00013936694,0.000012188407,0.0010501578,0.99029255,0.0056429706,0.0018519451],"study_design_scores_gemma":[0.0036427567,0.00021557562,0.00014843904,0.00006538797,0.00033575713,0.0000035118887,0.000153659,0.0015011274,0.00036153448,0.98917884,0.0039671357,0.0004262657],"about_ca_topic_score_codex":0.00008866336,"about_ca_topic_score_gemma":0.00002034954,"teacher_disagreement_score":0.20502979,"about_ca_system_score_codex":0.000053319804,"about_ca_system_score_gemma":0.00019852386,"threshold_uncertainty_score":0.9999278},"labels":[],"label_agreement":null},{"id":"W1984411764","doi":"10.1007/s00362-011-0380-7","title":"Inference for comparing a multinomial distribution with a known standard","year":2011,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Acadia University; Carleton University; York University; Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multinomial distribution; Mathematics; Statistics; Likelihood-ratio test; Test statistic; Estimator; Null distribution; Inference; Stochastic ordering; Score test; Econometrics; Applied mathematics; Statistical hypothesis testing; Computer science; Artificial intelligence","score_opus":0.11411823144706096,"score_gpt":0.3688814985691693,"score_spread":0.25476326712210834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984411764","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":[0.002005699,0.0000016757442,0.98107195,0.00005674299,0.000034839937,0.0004978825,0.0041108034,0.00012705951,0.012093364],"genre_scores_gemma":[0.7147189,5.681762e-7,0.28450382,0.000024230429,0.000017891656,0.00018547612,0.0004906518,0.000011970209,0.000046510875],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99893165,0.000031705542,0.0002994699,0.0002570851,0.00019915594,0.00028091777],"domain_scores_gemma":[0.9982172,0.0011519984,0.00008743289,0.0001773402,0.00018398797,0.00018202077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000134196,0.00015172538,0.00023677894,0.000018481463,0.00019247734,0.000032205677,0.00010757969,0.000052326093,0.00083191314],"category_scores_gemma":[0.00152353,0.00012365748,0.000035197343,0.0001156504,0.00019635854,0.0000507575,0.000022380815,0.000107371445,0.000036541733],"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":[0.00026502745,0.000086068336,0.0003412082,0.000050640945,0.000021193368,0.0000018208362,0.00010951196,0.0000018982936,0.000041211562,0.9912697,0.0021292977,0.005682415],"study_design_scores_gemma":[0.0061357957,0.0011747917,0.08510005,0.00015859408,0.00043024286,0.000017527269,0.00064820994,0.031070806,0.0009686044,0.8559135,0.017235367,0.0011464958],"about_ca_topic_score_codex":0.000021328957,"about_ca_topic_score_gemma":0.00004551103,"teacher_disagreement_score":0.7127132,"about_ca_system_score_codex":0.00008559135,"about_ca_system_score_gemma":0.000076098826,"threshold_uncertainty_score":0.9108866},"labels":[],"label_agreement":null},{"id":"W1985045737","doi":"10.1007/s00362-014-0623-5","title":"A diagnostic tool for regression analysis of complex survey data","year":2014,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","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; Wilfrid Laurier University","funders":"","keywords":"Nonparametric regression; Regression analysis; Statistics; Estimator; Nonparametric statistics; Plot (graphics); Mathematics; Regression diagnostic; Function (biology); Parametric statistics; Regression; Econometrics; Computer science; Polynomial regression","score_opus":0.08393571064839675,"score_gpt":0.36879003200034677,"score_spread":0.28485432135195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985045737","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":[0.00026741278,0.000013835006,0.9973609,0.00012053203,0.000084631974,0.00013429791,0.001038122,0.000023667675,0.00095662585],"genre_scores_gemma":[0.34971073,0.000004424106,0.6496323,0.00017253135,0.000014679801,0.0000058417054,0.00042376373,0.0000045906236,0.000031168784],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99848723,0.00039130892,0.00026723294,0.00044136803,0.00020697224,0.00020590606],"domain_scores_gemma":[0.98930454,0.009422513,0.00008537685,0.0010168934,0.00007865182,0.00009204793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014340499,0.00010499724,0.00035518061,0.00008429405,0.00006033575,0.000038974522,0.0008515708,0.000043744825,0.000052640567],"category_scores_gemma":[0.0062054708,0.00007874732,0.000053283613,0.00043518076,0.00008233423,0.000089394285,0.00024540065,0.000057598256,0.0000026480336],"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":[0.000025369942,0.00006671041,0.003100246,0.000042670406,0.00022239117,0.0000022134466,0.00008766727,0.000038138765,0.00049310055,0.576515,0.006417698,0.41298878],"study_design_scores_gemma":[0.00028111573,0.000101420825,0.28832713,0.000014669903,0.00024975123,5.033559e-7,0.0000017935755,0.6846809,0.000020788648,0.023882056,0.0022718168,0.00016808041],"about_ca_topic_score_codex":0.00007788939,"about_ca_topic_score_gemma":0.00010506367,"teacher_disagreement_score":0.68464273,"about_ca_system_score_codex":0.000008693751,"about_ca_system_score_gemma":0.000029743891,"threshold_uncertainty_score":0.7428976},"labels":[],"label_agreement":null},{"id":"W1985135770","doi":"10.1007/s00362-005-0272-9","title":"Pooling multivariate data under W, LR and LM tests","year":2006,"lang":"en","type":"article","venue":"Statistical Papers","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":"Carleton University","funders":"","keywords":"Mathematics; Statistics; Score test; Multivariate statistics; Multivariate normal distribution; Wald test; Estimator; Multivariate analysis of variance; Likelihood-ratio test; Pooling; Likelihood function; Quadratic equation; Covariance matrix; Maximum likelihood; Applied mathematics; Statistical hypothesis testing; Computer science","score_opus":0.16948770176197578,"score_gpt":0.45804618712040696,"score_spread":0.2885584853584312,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985135770","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":[0.000895382,0.000056032903,0.9882017,0.00019981283,0.000082346996,0.0001661371,0.00090037234,0.00008218809,0.009416057],"genre_scores_gemma":[0.24136356,0.0000072986104,0.75791025,0.00014065069,0.00007939835,0.000005947163,0.000084868094,0.00003028414,0.00037772552],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99844277,0.00013485615,0.00033186274,0.00049082004,0.0002270293,0.00037265566],"domain_scores_gemma":[0.99411756,0.005172619,0.00006309831,0.00045037357,0.000037880138,0.00015849277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004203749,0.00018831798,0.00028578026,0.000028742123,0.00012948667,0.000043974025,0.00017367456,0.000074638556,0.00017165039],"category_scores_gemma":[0.0029889399,0.00015659767,0.000016368256,0.000069065994,0.00021229387,0.00010068089,0.00018538555,0.00019213479,0.000014087245],"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":[0.000020271791,0.000062526284,0.00004356964,0.000053415613,0.000016391323,0.000029626413,0.000020984899,0.00003541062,0.0017237712,0.97227114,0.0009688628,0.02475403],"study_design_scores_gemma":[0.0004534058,0.000034362874,0.004108178,0.000026864325,0.00006908682,0.000010119771,0.000054535118,0.019019559,0.000020559717,0.97435445,0.0016150108,0.00023387389],"about_ca_topic_score_codex":0.00015967966,"about_ca_topic_score_gemma":0.0000950714,"teacher_disagreement_score":0.24046817,"about_ca_system_score_codex":0.000026039877,"about_ca_system_score_gemma":0.000027356335,"threshold_uncertainty_score":0.63858676},"labels":[],"label_agreement":null},{"id":"W1988200236","doi":"10.1007/s00362-005-0270-y","title":"Renyi's entropy for residual lifetime distribution","year":2006,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":44,"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":"Rényi entropy; Residual; Residual entropy; Statistical physics; Mathematics; Measure (data warehouse); Entropy (arrow of time); Statistics; Computer science; Principle of maximum entropy; Physics; Algorithm; Data mining; Configuration entropy; Quantum mechanics","score_opus":0.027615127799888003,"score_gpt":0.3387338489326748,"score_spread":0.31111872113278677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988200236","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":[0.0006555883,0.0000084575995,0.97449195,0.0014269982,0.00007061777,0.0004938676,0.01159514,0.00018645593,0.011070892],"genre_scores_gemma":[0.81108445,0.0000028219351,0.174817,0.00020071401,0.00032852998,0.0003907679,0.010411653,0.000038520517,0.0027255411],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986091,0.000049895058,0.00043052688,0.00029873932,0.0002680268,0.0003437096],"domain_scores_gemma":[0.99742734,0.0019945912,0.00009197836,0.00020936663,0.0001379285,0.00013878204],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00017837093,0.00016019156,0.00020457794,0.000020580199,0.00023887093,0.000053187727,0.00010870677,0.00008394988,0.0012447857],"category_scores_gemma":[0.0022181002,0.00015017705,0.000061257124,0.000120897435,0.0001945518,0.00003204082,0.000019714109,0.00009982972,0.00015603882],"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":[0.000028356833,0.00010956794,0.000021751295,0.00002864726,0.000008489309,0.0000013573441,0.0000042048473,0.0000047855783,0.00037715115,0.79875696,0.19946694,0.001191807],"study_design_scores_gemma":[0.00079101825,0.000071656985,0.010551958,0.000013136767,0.0000874382,0.000004042645,0.00002777583,0.0027068516,0.0002894459,0.8992381,0.08597131,0.00024725928],"about_ca_topic_score_codex":0.000027543212,"about_ca_topic_score_gemma":0.000014943436,"teacher_disagreement_score":0.81042886,"about_ca_system_score_codex":0.00010120488,"about_ca_system_score_gemma":0.0000462501,"threshold_uncertainty_score":0.99966824},"labels":[],"label_agreement":null},{"id":"W1989132167","doi":"10.1007/bf02762970","title":"Bayesian decision criteria in the presence of noises under quadratic and absolute value loss functions","year":2005,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Advanced Statistical Methods and Models","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":"Université de Moncton","funders":"","keywords":"Bayesian probability; Quadratic equation; Bayes' theorem; Mathematics; Bayes estimator; Computation; Value (mathematics); Sampling (signal processing); Applied mathematics; Hypergeometric function; Mathematical optimization; Computer science; Statistics; Algorithm; Mathematical analysis","score_opus":0.0639328150488618,"score_gpt":0.4206548436701531,"score_spread":0.3567220286212913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989132167","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":[0.0075266035,0.000060029375,0.98815805,0.0006343591,0.000055015033,0.00022466235,0.00014423789,0.000014032705,0.00318304],"genre_scores_gemma":[0.5342286,0.000015774423,0.46546343,0.00018389746,0.000019894787,0.00001404608,0.0000025077306,0.0000090002895,0.00006281991],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986245,0.00022810463,0.00039647048,0.00024009722,0.00027272204,0.00023810276],"domain_scores_gemma":[0.99064684,0.008927628,0.00005924675,0.00023935767,0.00003718119,0.00008976537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040045363,0.00013391908,0.00024862104,0.000041545467,0.00008524824,0.000024868064,0.0001211675,0.000054839173,0.00023484392],"category_scores_gemma":[0.0029355243,0.00008979419,0.00002774952,0.00011748891,0.0003118343,0.000100792,0.0000394316,0.0001630553,0.0000053747067],"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":[0.00006227368,0.00011573809,0.000026202273,0.000059890608,0.000010490804,0.000010816313,0.0004911106,0.00030799073,0.00044372608,0.95835197,0.0005691942,0.039550576],"study_design_scores_gemma":[0.00039056226,0.00011046034,0.006064666,0.00007423006,0.000047608013,0.000012241453,0.0005832218,0.023757536,0.000017665681,0.9683004,0.00050107867,0.00014030997],"about_ca_topic_score_codex":0.000025579522,"about_ca_topic_score_gemma":0.00019966763,"teacher_disagreement_score":0.526702,"about_ca_system_score_codex":0.000023451606,"about_ca_system_score_gemma":0.00002583083,"threshold_uncertainty_score":0.3661701},"labels":[],"label_agreement":null},{"id":"W1992656431","doi":"10.1007/s00362-012-0448-z","title":"Group sequential methods based on ranked set samples","year":2012,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","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 Windsor","funders":"","keywords":"RSS; Computer science; Simple random sample; Sample (material); Set (abstract data type); Sample size determination; Statistics; Sampling (signal processing); Group (periodic table); Group testing; Population; Data mining; Mathematics; Medicine","score_opus":0.17366085428668596,"score_gpt":0.467720133005085,"score_spread":0.2940592787183991,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992656431","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":[0.00027571278,0.000005990849,0.9768692,0.00041552042,0.00015569742,0.0002695121,0.0019876207,0.00016570874,0.019854983],"genre_scores_gemma":[0.5105931,6.8455137e-7,0.4880558,0.00058488734,0.00006906514,0.000078570265,0.00053488405,0.000019093146,0.000063913256],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983132,0.00032374423,0.0003620201,0.000239428,0.0003322719,0.0004293389],"domain_scores_gemma":[0.99437577,0.00484089,0.000077506375,0.0002948488,0.000051257783,0.00035974834],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00059386814,0.00018969201,0.00024111882,0.00004859725,0.00018716007,0.00003679952,0.00012264331,0.000086511776,0.006619342],"category_scores_gemma":[0.003360324,0.00016539791,0.00007071886,0.00017799153,0.00020959348,0.000054483007,0.000022739301,0.0001821388,0.00033201606],"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":[0.00003394044,0.00020676096,0.000069661335,0.000036413232,0.000020612357,0.0000010801725,0.000041575488,0.000006069796,0.00078153337,0.98282534,0.0082868375,0.007690173],"study_design_scores_gemma":[0.0027377652,0.00025618894,0.04399859,0.000067087094,0.0004131563,0.000011598253,0.00030888407,0.038722605,0.0011122819,0.83435506,0.07690088,0.0011159388],"about_ca_topic_score_codex":0.000011167289,"about_ca_topic_score_gemma":0.0000025766624,"teacher_disagreement_score":0.5103174,"about_ca_system_score_codex":0.00008691993,"about_ca_system_score_gemma":0.00003006915,"threshold_uncertainty_score":0.99428874},"labels":[],"label_agreement":null},{"id":"W1995436618","doi":"10.1007/bf02926010","title":"Imputation by power transformation","year":2003,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":110,"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 Northern British Columbia","funders":"","keywords":"Imputation (statistics); Estimator; Mean squared error; Statistics; Population mean; Mathematics; Econometrics; Missing data","score_opus":0.0340552416612756,"score_gpt":0.3409253376143045,"score_spread":0.3068700959530289,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995436618","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":[0.005987993,0.0000112554835,0.90769154,0.00010837481,0.00007253298,0.00014563774,0.00008466328,0.00023981003,0.08565822],"genre_scores_gemma":[0.8523476,0.0000039110355,0.1472603,0.00011405375,0.0000039738325,0.00001723122,0.00006814477,0.000014789181,0.00017001297],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99922854,0.00010046639,0.0002242607,0.00011697278,0.00017722322,0.00015252423],"domain_scores_gemma":[0.9990957,0.00066309184,0.000040354887,0.000093305134,0.0000411926,0.000066382396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040468818,0.00008982679,0.00010637711,0.000030662475,0.00008404861,0.000026373851,0.000039140636,0.000057486937,0.00078798813],"category_scores_gemma":[0.0012514091,0.00008125253,0.0000250443,0.00007940989,0.000042083677,0.00007557609,0.000002017466,0.00008086848,0.00005031871],"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":[0.000009844766,0.00005417182,0.00005534008,0.000031691732,0.000011470944,8.906965e-7,0.00047235153,0.000003932321,0.0009930589,0.9669734,0.022479808,0.0089140115],"study_design_scores_gemma":[0.00045253822,0.00013371572,0.000572064,0.000021369859,0.000027764921,0.000009055773,0.00033925852,0.00048006896,0.0036747644,0.9702014,0.023788104,0.00029989806],"about_ca_topic_score_codex":0.000007902128,"about_ca_topic_score_gemma":0.0000020593293,"teacher_disagreement_score":0.8463596,"about_ca_system_score_codex":0.00003263979,"about_ca_system_score_gemma":0.000018305565,"threshold_uncertainty_score":0.8627917},"labels":[],"label_agreement":null},{"id":"W1996133602","doi":"10.1007/s00362-007-0361-4","title":"A practical sampling approach for a Bayesian mixture model with unknown number of components","year":2007,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","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 Manitoba","funders":"","keywords":"Approximate Bayesian computation; Computation; Computer science; Bayesian probability; Bayesian inference; Mixture model; Multiplicative function; Algorithm; Sampling (signal processing); Markov chain Monte Carlo; Inference; Gibbs sampling; Bayesian statistics; Mathematics; Artificial intelligence","score_opus":0.04849651572576249,"score_gpt":0.3555198557031111,"score_spread":0.30702333997734865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996133602","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":[0.00010671883,0.000007034936,0.9821409,0.00026756947,0.00004895793,0.00033445956,0.000037781294,0.000053275184,0.017003275],"genre_scores_gemma":[0.20570004,0.0000011666343,0.79386175,0.00025062347,0.000030660372,0.00001565454,0.000017911596,0.000017331522,0.00010486268],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99826264,0.000067166424,0.00032820605,0.0004927212,0.0003673572,0.0004819011],"domain_scores_gemma":[0.99827385,0.00087596866,0.00010484297,0.00036378048,0.00011768712,0.00026388525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073547557,0.00019875317,0.00032789056,0.000045310673,0.00009810593,0.000046515597,0.00030645158,0.00012020927,0.000011645516],"category_scores_gemma":[0.00018799545,0.00014945898,0.000066193694,0.00019954279,0.00015843612,0.0001446997,0.000072173934,0.00023150949,0.0000015024622],"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":[0.00015909015,0.00017252032,0.00006257053,0.00007980292,0.000038191232,0.000010824013,0.00021384699,0.00017802333,0.0011542427,0.9782174,0.00025346383,0.019459995],"study_design_scores_gemma":[0.0010321815,0.00014757278,0.000420038,0.000029084165,0.00005789022,0.00008858364,0.000028863822,0.8824132,0.00026223328,0.11444918,0.0007068876,0.00036426567],"about_ca_topic_score_codex":0.000009387675,"about_ca_topic_score_gemma":0.000003873722,"teacher_disagreement_score":0.88223517,"about_ca_system_score_codex":0.000033209344,"about_ca_system_score_gemma":0.00011022244,"threshold_uncertainty_score":0.60947603},"labels":[],"label_agreement":null},{"id":"W1996588625","doi":"10.1007/s00362-008-0163-y","title":"Preliminary test estimation of the parameters of exponential and Pareto distributions for censored samples","year":2008,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Florida International University","keywords":"Estimator; Pareto principle; Statistics; Mathematics; Exponential function; Null hypothesis; Exponential distribution; Pareto distribution; Efficiency; Range (aeronautics); Sample (material); Econometrics; Applied mathematics; Engineering; Physics","score_opus":0.058144987851130626,"score_gpt":0.33072742101925034,"score_spread":0.2725824331681197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996588625","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":[0.05806777,0.000008868235,0.9290523,0.00033932543,0.000033791148,0.00054779544,0.011692132,0.000025200932,0.00023284988],"genre_scores_gemma":[0.8107301,0.0000049109026,0.18883742,0.000015048542,0.000005374292,0.00008593095,0.0002915821,0.00000775307,0.000021900149],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99900544,0.000043313332,0.0004376456,0.00016479241,0.00019897682,0.00014986239],"domain_scores_gemma":[0.9949174,0.004502708,0.00017425766,0.00020416218,0.00012180335,0.00007970198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000947752,0.00010673219,0.00021106926,0.00002133999,0.00020343094,0.000006100099,0.00009821524,0.00005175517,0.000068759786],"category_scores_gemma":[0.007445003,0.00008227183,0.00006156193,0.00013208836,0.00074585405,0.00003160319,0.00003225623,0.00006240706,0.0000014689587],"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":[0.00004711411,0.0002093274,0.00056638307,0.00014948557,0.000021451802,3.4279452e-7,0.00012041196,0.000048466733,0.0013464694,0.9921455,0.0027189008,0.0026261602],"study_design_scores_gemma":[0.0016082033,0.0004499356,0.44769496,0.00012328786,0.00038244828,0.00003114339,0.00033015068,0.048499476,0.007882869,0.49225265,0.00038809955,0.00035678604],"about_ca_topic_score_codex":0.000016189715,"about_ca_topic_score_gemma":0.0000034159907,"teacher_disagreement_score":0.7526623,"about_ca_system_score_codex":0.000023687933,"about_ca_system_score_gemma":0.00004820188,"threshold_uncertainty_score":0.8912902},"labels":[],"label_agreement":null},{"id":"W1997914622","doi":"10.1007/s00362-002-0122-y","title":"The product and quotient of general beta distributions","year":2002,"lang":"en","type":"article","venue":"Statistical Papers","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":"Université de Moncton","funders":"","keywords":"BETA (programming language); Quotient; Mathematics; Beta distribution; Hypergeometric distribution; Product (mathematics); Computation; Interval (graph theory); Reliability (semiconductor); Hypergeometric function; Beta function (physics); Applied mathematics; Discrete mathematics; Combinatorics; Computer science; Pure mathematics; Statistics; Algorithm; Physics","score_opus":0.047931806919987295,"score_gpt":0.32626509025291867,"score_spread":0.2783332833329314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997914622","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":[0.009132864,0.0002733835,0.9136847,0.008411047,0.00016229572,0.00081618613,0.005591242,0.00013299618,0.061795235],"genre_scores_gemma":[0.9759394,0.000048284986,0.02292662,0.000043187552,0.000028898186,0.000051884384,0.000086387285,0.000008660985,0.0008666637],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990967,0.000051269035,0.0003021985,0.00016769466,0.00019678823,0.00018537436],"domain_scores_gemma":[0.9983124,0.0012026053,0.00006989818,0.00021565263,0.00008419705,0.00011523333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012265197,0.00009154934,0.00012771625,0.000012279935,0.00028362224,0.000026920843,0.00008759248,0.000023746856,0.0006372782],"category_scores_gemma":[0.0014791556,0.00006321872,0.000026623728,0.00012400202,0.0004973757,0.000021882537,0.0000309095,0.00008939478,0.00003188954],"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":[0.000002811843,0.000071751005,0.0000584367,0.000017313207,0.000013058213,4.9765146e-7,0.00002399609,6.927772e-7,0.00018143051,0.96878767,0.019175353,0.0116669815],"study_design_scores_gemma":[0.0009951461,0.00017352906,0.08489608,0.00003663158,0.0002392821,0.00002621762,0.00019808608,0.020351158,0.00087804074,0.7851191,0.10657184,0.0005148537],"about_ca_topic_score_codex":0.000007702272,"about_ca_topic_score_gemma":0.0000053821814,"teacher_disagreement_score":0.96680653,"about_ca_system_score_codex":0.000023748611,"about_ca_system_score_gemma":0.000010073498,"threshold_uncertainty_score":0.69777495},"labels":[],"label_agreement":null},{"id":"W2000183763","doi":"10.1007/s00362-012-0457-y","title":"Measures of tail asymmetry for bivariate copulas","year":2012,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","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 British Columbia","funders":"","keywords":"Copula (linguistics); Bivariate analysis; Asymmetry; Tail dependence; Univariate; Skewness; Econometrics; Mathematics; Statistics; Extreme value theory; Statistical physics; Multivariate statistics; Physics","score_opus":0.08468178149611831,"score_gpt":0.2714745427006765,"score_spread":0.18679276120455818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000183763","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":[0.053222094,0.002261141,0.8883966,0.00019854259,0.0010340059,0.00039626492,0.0027212661,0.00004092519,0.051729154],"genre_scores_gemma":[0.97537917,0.000036864192,0.024163902,0.000083767925,0.00010644992,0.000015339252,0.000031104086,0.000016419888,0.00016701047],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989869,0.000010541107,0.0004604871,0.00018124761,0.000040167753,0.00032068312],"domain_scores_gemma":[0.9993537,0.00022917226,0.00012795064,0.00015200944,0.000031908294,0.00010522946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057383644,0.00009738134,0.00031305532,0.00007003098,0.00006420425,0.000010961451,0.00008980436,0.00007913943,0.00024007895],"category_scores_gemma":[0.0011049832,0.000105492734,0.00007921786,0.00009557947,0.000069033296,0.0000861758,0.000020007097,0.00007808309,0.000079227095],"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":[0.000041865016,0.00006556509,0.04138699,0.00005124495,0.000023762448,1.3687749e-7,0.00017828637,0.000019843988,0.000090734175,0.9507757,0.0007033916,0.0066624777],"study_design_scores_gemma":[0.0019099724,0.00035117072,0.31552333,0.00003892242,0.000060594542,0.0000015365508,0.00021622678,0.015170238,0.0004603627,0.46663576,0.19882074,0.0008111346],"about_ca_topic_score_codex":0.00021795783,"about_ca_topic_score_gemma":0.000012273541,"teacher_disagreement_score":0.92215705,"about_ca_system_score_codex":0.000035697743,"about_ca_system_score_gemma":0.000014545588,"threshold_uncertainty_score":0.43018687},"labels":[],"label_agreement":null},{"id":"W2006247731","doi":"10.1007/bf02762967","title":"An asymptotic theory for semiparametric generalized least squares estimation in partially linear regression models","year":2005,"lang":"en","type":"article","venue":"Statistical Papers","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 Calgary","funders":"","keywords":"Mathematics; Asymptotic analysis; Semiparametric regression; Moment (physics); Heteroscedasticity; Applied mathematics; Least-squares function approximation; Generalized least squares; Asymptotic distribution; Semiparametric model; Total least squares; Regression; Econometrics; Statistics; Estimator","score_opus":0.08774102508667554,"score_gpt":0.43880236778422316,"score_spread":0.35106134269754763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006247731","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":[0.00539074,0.00006035087,0.9923488,0.00013930578,0.00007668672,0.0006495521,0.0002727891,0.000102509264,0.00095930125],"genre_scores_gemma":[0.36030492,0.000011962341,0.6391704,0.00013254295,0.00006415305,0.00010211295,0.00006151124,0.00003938251,0.00011301426],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975669,0.00043411765,0.00063787535,0.0005062705,0.00033858433,0.0005162464],"domain_scores_gemma":[0.99423575,0.004932782,0.00013033241,0.00034122157,0.000095556374,0.00026435146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009980109,0.00027602894,0.00047133022,0.00014725381,0.00012675775,0.000037533442,0.00017421404,0.00015280851,0.00016621889],"category_scores_gemma":[0.0048352345,0.000222674,0.00006967868,0.00021565794,0.00014279062,0.00026598404,0.000027997328,0.00021980728,0.000010197565],"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":[0.000312633,0.00020898416,0.000007848126,0.00008053455,0.0000126805635,0.000005414893,0.00022327209,0.07198083,0.0005175028,0.7724423,0.00011517759,0.15409283],"study_design_scores_gemma":[0.000659775,0.00013657435,0.000049383318,0.000039332335,0.0000351182,0.0000016481107,0.000042566477,0.49049807,0.00011903604,0.5081575,0.00009591886,0.00016509542],"about_ca_topic_score_codex":0.000009083642,"about_ca_topic_score_gemma":0.00005897309,"teacher_disagreement_score":0.41851723,"about_ca_system_score_codex":0.00011662019,"about_ca_system_score_gemma":0.00006399541,"threshold_uncertainty_score":0.9080382},"labels":[],"label_agreement":null},{"id":"W2006374531","doi":"10.1007/s00362-009-0240-x","title":"A generalized skew two-piece skew-normal distribution","year":2009,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":30,"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","keywords":"Skew; Generalization; Simple (philosophy); Distribution (mathematics); Mathematics; Class (philosophy); Skew normal distribution; Moment (physics); Representation (politics); Function (biology); Mathematical analysis; Applied mathematics; Pure mathematics; Computer science; Physics; Classical mechanics; Artificial intelligence","score_opus":0.03632922308416797,"score_gpt":0.3647984042046783,"score_spread":0.3284691811205103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006374531","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":[0.0024165127,0.0000149878915,0.96767426,0.00209306,0.00007832538,0.0003245711,0.0030159194,0.00028103337,0.024101343],"genre_scores_gemma":[0.86163443,0.000008877373,0.13412634,0.0010707683,0.0001074975,0.00006264539,0.0023259067,0.000019110163,0.00064440834],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981123,0.00010483619,0.0005222058,0.00037028125,0.00042811182,0.00046222683],"domain_scores_gemma":[0.9983263,0.00075568474,0.000110875655,0.0003258534,0.00013134927,0.00034993968],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00020989696,0.00023770284,0.00029793254,0.000031798667,0.00028359416,0.00007730559,0.00017975406,0.00013030357,0.0031835523],"category_scores_gemma":[0.0018678125,0.00022124869,0.00008496889,0.0002833394,0.0001872141,0.00008320914,0.000025390857,0.00030912404,0.00040354312],"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":[0.000029833092,0.00018237722,0.000015805752,0.00001489448,0.000014236397,0.0000088340685,0.000026256119,0.0000059763147,0.0006203675,0.9558284,0.024998307,0.018254675],"study_design_scores_gemma":[0.0014376588,0.00011033268,0.020724628,0.000023195651,0.00010999544,0.0000199138,0.000034841607,0.005768325,0.0002195419,0.94963145,0.02149267,0.000427475],"about_ca_topic_score_codex":0.000018307108,"about_ca_topic_score_gemma":0.0000065251793,"teacher_disagreement_score":0.85921794,"about_ca_system_score_codex":0.00013028043,"about_ca_system_score_gemma":0.00006479248,"threshold_uncertainty_score":0.9977277},"labels":[],"label_agreement":null},{"id":"W2007738022","doi":"10.1007/s003620100073","title":"On the comparison of the pre-test and shrinkage estimators for the univariate normal mean","year":2001,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Estimator; Univariate; Statistics; Shrinkage estimator; Mathematics; Mean squared error; Shrinkage; Sample (material); Variance (accounting); Sample size determination; Population; Population mean; Econometrics; Minimum-variance unbiased estimator; Efficient estimator; Multivariate statistics","score_opus":0.0796369323591667,"score_gpt":0.4147179015500356,"score_spread":0.3350809691908689,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007738022","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":[0.00660265,0.000023095063,0.98608416,0.0012261111,0.000108281616,0.00068206294,0.000322886,0.00002185645,0.0049289204],"genre_scores_gemma":[0.8161298,0.0000094970455,0.18319002,0.00022784676,0.000027330407,0.00004332388,0.0000023535401,0.000022614955,0.00034719394],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99881756,0.00014330822,0.00032206537,0.00019636795,0.0002541954,0.00026652563],"domain_scores_gemma":[0.96779317,0.031619687,0.00011765452,0.0003483913,0.000046705667,0.00007437698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004816729,0.00015818293,0.0002543722,0.000011157458,0.000332628,0.000024830497,0.00024814624,0.000048920516,0.00011373507],"category_scores_gemma":[0.0067438404,0.000068557114,0.000055186545,0.00008806195,0.00049151515,0.000025059073,0.00007823539,0.00022595652,0.0000015423344],"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":[0.00007306818,0.00008153197,0.0001998624,0.00004146481,0.000028231625,0.0000011026397,0.00044774433,0.00015014192,0.00018508248,0.98618513,0.0007505658,0.011856053],"study_design_scores_gemma":[0.00042280098,0.00023710156,0.0042453636,0.000047973408,0.0001523554,0.000004104102,0.0003872472,0.06991538,0.00016390807,0.9223415,0.0019417233,0.00014054678],"about_ca_topic_score_codex":0.000024194082,"about_ca_topic_score_gemma":0.00005204671,"teacher_disagreement_score":0.80952716,"about_ca_system_score_codex":0.000018960525,"about_ca_system_score_gemma":0.000025219279,"threshold_uncertainty_score":0.8073494},"labels":[],"label_agreement":null},{"id":"W2007786637","doi":"10.1007/s00362-013-0551-9","title":"On the central limit theorem along subsequences of sums of i.i.d. random variables","year":2013,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":0,"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 New Brunswick; Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Subsequence; Combinatorics; Sequence (biology); Random variable; Longest increasing subsequence; Central limit theorem; Physics; Mathematics; Mathematical analysis; Statistics","score_opus":0.05820097930101838,"score_gpt":0.3150263281969482,"score_spread":0.25682534889592984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007786637","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":[0.8554362,0.00013528575,0.06876004,0.0033605662,0.00043218286,0.0009557979,0.00040029528,0.000029520772,0.07049009],"genre_scores_gemma":[0.99688303,0.000020637273,0.0027139187,0.00017542377,0.000016193479,0.000013098018,0.0000033029473,0.0000049853315,0.00016941805],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99720556,0.0005202432,0.0006686048,0.00029723966,0.0010126536,0.00029570697],"domain_scores_gemma":[0.98120743,0.017843524,0.00018236821,0.0004540419,0.00019869443,0.00011392004],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002134609,0.00011938761,0.0003486801,0.00004772832,0.00010109257,0.00006183952,0.0006464644,0.00006567149,0.0049862545],"category_scores_gemma":[0.010257608,0.00005451169,0.00010310224,0.00025977776,0.0012198765,0.00011644587,0.00005929558,0.00013379015,0.00009192322],"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":[0.00012519718,0.00005426964,0.0017658911,0.000008163661,0.000021565726,0.000001320377,0.0005024403,0.00041135374,0.0017312465,0.9837973,0.0019904815,0.00959077],"study_design_scores_gemma":[0.00039055126,0.00012649517,0.019301772,0.000022074439,0.000015394791,0.0000011168888,0.0007390421,0.003271374,0.00095319544,0.974883,0.00021047401,0.00008551769],"about_ca_topic_score_codex":0.00069804053,"about_ca_topic_score_gemma":0.00012050578,"teacher_disagreement_score":0.1414468,"about_ca_system_score_codex":0.000015120362,"about_ca_system_score_gemma":0.00009232579,"threshold_uncertainty_score":0.9980794},"labels":[],"label_agreement":null},{"id":"W2008617867","doi":"10.1007/s00362-008-0187-3","title":"Exact expression of the density of the sample generalized variance and applications","year":2008,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Advanced Statistical Methods and Models","field":"Mathematics","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":"Université de Moncton","funders":"","keywords":"Mathematics; Statistics; Covariance matrix; Multivariate normal distribution; Confidence interval; Expression (computer science); Covariance; Multivariate statistics; Estimation of covariance matrices; Sample (material); Exact statistics; Probability density function; Applied mathematics; Computer science; Physics","score_opus":0.07229338260678614,"score_gpt":0.37005928614056244,"score_spread":0.2977659035337763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008617867","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":[0.013065032,0.000019567718,0.98511535,0.00007164802,0.000034624787,0.0003022405,0.00036025298,0.000008549205,0.0010227633],"genre_scores_gemma":[0.44867483,0.000020109948,0.55112976,0.000049353122,0.0000127487265,0.000018682274,0.0000013995785,0.000007540776,0.000085588224],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990998,0.0001666885,0.00025193737,0.00015543918,0.00020438453,0.00012174181],"domain_scores_gemma":[0.99667627,0.0027454232,0.00012624083,0.0003411485,0.000057222085,0.000053673502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013603002,0.00008590451,0.00020793495,0.0000072710995,0.00016725877,0.0000022240924,0.00013581767,0.000040868337,0.00005665163],"category_scores_gemma":[0.002106118,0.000045920242,0.000041866184,0.00008640401,0.0005160341,0.000017997774,0.000093915725,0.00010547605,3.159999e-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":[0.00002280411,0.00005470145,0.0008756492,0.00007784612,0.000008542787,4.5642022e-7,0.00015507727,0.000018088826,0.02574855,0.96919096,0.00022080776,0.0036265394],"study_design_scores_gemma":[0.0002976275,0.000020003337,0.019378245,0.000034682842,0.00004146245,0.000005829122,0.00003331433,0.00041482452,0.008402117,0.97044617,0.0008424133,0.00008333409],"about_ca_topic_score_codex":0.000032629177,"about_ca_topic_score_gemma":0.000009223622,"teacher_disagreement_score":0.4356098,"about_ca_system_score_codex":0.000010976232,"about_ca_system_score_gemma":0.000032495485,"threshold_uncertainty_score":0.2521372},"labels":[],"label_agreement":null},{"id":"W2009109739","doi":"10.1007/s00362-008-0148-x","title":"Life expectancy of a bathtub shaped failure distribution","year":2008,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Probabilistic and Robust Engineering Design","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":"Western University","funders":"","keywords":"Bathtub; Weibull distribution; Life expectancy; Parametric statistics; Residual; Reliability (semiconductor); Confidence interval; Statistics; Reliability engineering; Failure rate; Mathematics; Computer science; Econometrics; Engineering; Algorithm; Demography; Geography; Sociology","score_opus":0.06641643713144421,"score_gpt":0.30814972472064694,"score_spread":0.24173328758920273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009109739","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":[0.011940861,0.00010746723,0.98195094,0.00042502998,0.00021329414,0.00015155794,0.0004419147,0.000066127024,0.004702803],"genre_scores_gemma":[0.9848591,0.000008904519,0.014592007,0.00006691639,0.000050685656,0.000009248475,0.00003441542,0.000008896871,0.00036983786],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9978694,0.00009370866,0.0005489143,0.00033827787,0.00089552026,0.0002542105],"domain_scores_gemma":[0.9972213,0.0018723726,0.000095592586,0.0003294647,0.00016747059,0.00031383018],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00044602586,0.00013201039,0.00031214752,0.00005404151,0.00011307954,0.00002004745,0.000317977,0.00007989265,0.0015260737],"category_scores_gemma":[0.020638332,0.00009449134,0.000076057004,0.00040251485,0.00033096282,0.00007357568,0.000047304744,0.00012736414,0.00016770292],"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":[0.00022944943,0.0003411086,0.0050254394,0.000056696885,0.00008866301,0.0002154894,0.0013341781,0.0024126745,0.007589174,0.75310326,0.21877812,0.010825767],"study_design_scores_gemma":[0.0062769097,0.0019997929,0.42053142,0.00022191057,0.00025286197,0.0003172567,0.004935729,0.14008643,0.0009154799,0.25272378,0.16865765,0.0030807592],"about_ca_topic_score_codex":0.00000907728,"about_ca_topic_score_gemma":0.0000028030872,"teacher_disagreement_score":0.9729182,"about_ca_system_score_codex":0.000033478093,"about_ca_system_score_gemma":0.0001754244,"threshold_uncertainty_score":0.99938667},"labels":[],"label_agreement":null},{"id":"W2010905041","doi":"10.1007/s00362-010-0307-8","title":"Bayesian and Robust Bayesian analysis under a general class of balanced loss functions","year":2010,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":50,"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","keywords":"Omega; Estimator; Mathematics; Bayesian probability; Combinatorics; Mean squared error; Bayes estimator; Statistics; Physics","score_opus":0.02455193496329103,"score_gpt":0.31785220483004795,"score_spread":0.2933002698667569,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010905041","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":[0.008584438,0.0000028287234,0.9793868,0.0007265109,0.00005967561,0.00016572414,0.0018440798,0.00006448375,0.009165468],"genre_scores_gemma":[0.8598948,0.0000026494301,0.13920207,0.0001148592,0.0000309903,0.000034984823,0.00030025488,0.000013639237,0.00040571805],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99873114,0.00005201882,0.00042235389,0.00030300225,0.00025059545,0.00024087098],"domain_scores_gemma":[0.9982415,0.0009627722,0.00011022517,0.0003027806,0.000119050914,0.00026369316],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00014103271,0.00015773262,0.0003234299,0.0001005135,0.00015651026,0.000034462206,0.00009699426,0.00010607077,0.0034282908],"category_scores_gemma":[0.0007811499,0.00014372665,0.000080249294,0.00051596266,0.00046826134,0.00004234072,0.000029490433,0.00023251266,0.000019216548],"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":[0.000012876417,0.00013148818,0.0009014401,0.00003067366,0.00015920919,0.0000020016312,0.000027805754,0.00020010624,0.0014166787,0.9941415,0.0015002814,0.0014759231],"study_design_scores_gemma":[0.0013053024,0.000121454286,0.20549932,0.000015531408,0.0018440203,0.000018653069,0.00036892502,0.2846639,0.0001252657,0.5034287,0.0019889872,0.00061999075],"about_ca_topic_score_codex":0.00003481711,"about_ca_topic_score_gemma":0.0002572595,"teacher_disagreement_score":0.8513104,"about_ca_system_score_codex":0.000023674182,"about_ca_system_score_gemma":0.000046490768,"threshold_uncertainty_score":0.9974827},"labels":[],"label_agreement":null},{"id":"W2012720419","doi":"10.1007/s003620100050","title":"Order statistics from non-identical right-truncated Lomax random variables with applications","year":2001,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":42,"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; McMaster University","keywords":"Order statistic; Outlier; Mathematics; Independent and identically distributed random variables; Statistics; Lomax distribution; Simple random sample; Simple (philosophy); Random variable; Robustness (evolution); Order (exchange); Maximum likelihood","score_opus":0.01826528234301331,"score_gpt":0.3092817469876108,"score_spread":0.29101646464459746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012720419","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":[0.00045577326,0.000010181706,0.9699079,0.0005136564,0.00005571739,0.00091089535,0.00664463,0.00024872596,0.021252554],"genre_scores_gemma":[0.2653455,0.00002516173,0.7283446,0.0004208369,0.00013464502,0.0007035894,0.0038082157,0.00007418917,0.0011432032],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99727756,0.00011136978,0.00078440603,0.0006292768,0.0006428333,0.0005545476],"domain_scores_gemma":[0.994149,0.004187014,0.00018545901,0.0005735882,0.00042033373,0.00048454799],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00021004511,0.0003714982,0.000506232,0.00007287348,0.00041460324,0.0001482223,0.00029147617,0.00015317589,0.01094494],"category_scores_gemma":[0.0013920027,0.0003022344,0.000048124715,0.00065928616,0.0005550225,0.0000984995,0.00005354276,0.0003220671,0.0008597637],"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":[0.00016915209,0.0003952444,0.00021970471,0.000036354173,0.00011447458,0.000044464694,0.000043011714,0.000034743836,0.00027630816,0.98132217,0.0143655455,0.0029788187],"study_design_scores_gemma":[0.004508647,0.00013412313,0.011803585,0.00006136182,0.0006128456,0.000046263933,0.00019406756,0.028603552,0.00010073574,0.90665084,0.046425484,0.0008584657],"about_ca_topic_score_codex":0.00013974671,"about_ca_topic_score_gemma":0.000117468786,"teacher_disagreement_score":0.26488975,"about_ca_system_score_codex":0.00011609678,"about_ca_system_score_gemma":0.00017119231,"threshold_uncertainty_score":0.99994296},"labels":[],"label_agreement":null},{"id":"W2020172162","doi":"10.1007/s00362-006-0328-5","title":"2 m 41 designs with minimum aberration or weak minimum aberration","year":2007,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","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 Waterloo","funders":"Nankai University; National Natural Science Foundation of China","keywords":"Mathematics; Zhàng; Combinatorics; Discrete mathematics","score_opus":0.13212961033756035,"score_gpt":0.4336010623331525,"score_spread":0.3014714519955921,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020172162","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":[0.0146192135,0.000038594826,0.8481829,0.00035236226,0.00052399666,0.00054493395,0.000050662537,0.000095333955,0.13559197],"genre_scores_gemma":[0.5642779,0.000003311927,0.426563,0.00046835837,0.0001236186,0.00002321572,0.000028331682,0.000033840533,0.008478472],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9950534,0.00052993314,0.0009614679,0.00084665365,0.0019791326,0.00062938244],"domain_scores_gemma":[0.9923096,0.0062052687,0.0002457087,0.0005399696,0.00026198858,0.0004374916],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0040661464,0.00031643617,0.0004237961,0.00023125566,0.00028105057,0.00031405705,0.00045617486,0.00016838867,0.0048498255],"category_scores_gemma":[0.004758219,0.00020314861,0.00006874556,0.0009030093,0.00047471732,0.00042284795,0.00006244923,0.00023785056,0.0006924746],"study_design_candidate":"bench_or_experimental","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":[0.0077339755,0.0007172558,0.0027384555,0.00003253649,0.00014033394,0.00047602705,0.0040407414,0.00036671918,0.54109174,0.11767547,0.06023729,0.26474944],"study_design_scores_gemma":[0.018650955,0.02721701,0.28242117,0.00038053162,0.0007375834,0.0007411949,0.08827372,0.065852225,0.15393509,0.13978471,0.21350802,0.008497788],"about_ca_topic_score_codex":0.000039801784,"about_ca_topic_score_gemma":0.00025725976,"teacher_disagreement_score":0.54965866,"about_ca_system_score_codex":0.00014807409,"about_ca_system_score_gemma":0.00021035201,"threshold_uncertainty_score":0.9960599},"labels":[],"label_agreement":null},{"id":"W2021336536","doi":"10.1007/s00362-013-0572-4","title":"The estimation and inference on the equal ratios of means to standard deviations of normal populations","year":2013,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Advanced Statistical Methods and Models","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":"York University","funders":"National Natural Science Foundation of China","keywords":"Standard deviation; Statistics; Mathematics; Standard error; Inference; Estimation; Population; Maximum likelihood; Likelihood-ratio test; Sample size determination; Normal population; Statistical hypothesis testing; Value (mathematics); Econometrics; Computer science; Economics","score_opus":0.12028968574899306,"score_gpt":0.4337729070999138,"score_spread":0.3134832213509207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021336536","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":[0.0061707916,0.000004445212,0.98894936,0.0010698355,0.0000351905,0.0004637324,0.0003180046,0.00001034949,0.0029782907],"genre_scores_gemma":[0.5922234,0.0000027688586,0.40762508,0.000056719997,0.0000053406457,0.000041345913,0.0000043652876,0.0000057098905,0.000035261863],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989379,0.00014651896,0.00037617973,0.00011768286,0.00027167116,0.00015001511],"domain_scores_gemma":[0.9904834,0.008968956,0.00010582142,0.00019430197,0.00016650552,0.00008098688],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00033217118,0.00009214299,0.00016848663,0.00002320553,0.00020313279,0.000024165722,0.000089586254,0.000029178571,0.00014420121],"category_scores_gemma":[0.010978858,0.000051353676,0.00002045989,0.000098734854,0.00021539249,0.000055244593,0.00003367358,0.00009806707,0.0000053960994],"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":[0.00001934628,0.000016835926,0.000042950796,0.000020135512,0.00000988372,1.0771613e-7,0.0002888227,0.0005562584,0.0003299672,0.96253437,0.00028595328,0.035895392],"study_design_scores_gemma":[0.000116929055,0.00019766786,0.0030848342,0.0000298269,0.000029148294,3.1348628e-7,0.00026331184,0.024672603,0.00017199942,0.97126114,0.000101361606,0.00007088311],"about_ca_topic_score_codex":0.000030721912,"about_ca_topic_score_gemma":0.00007992342,"teacher_disagreement_score":0.5860526,"about_ca_system_score_codex":0.000018592957,"about_ca_system_score_gemma":0.000034979163,"threshold_uncertainty_score":0.99735206},"labels":[],"label_agreement":null},{"id":"W2024653850","doi":"10.1007/s00362-007-0096-x","title":"Testing interaction in some predator–prey populations","year":2007,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Mathematical and Theoretical Epidemiology and Ecology Models","field":"Medicine","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 Windsor","funders":"","keywords":"Ode; Ordinary differential equation; Applied mathematics; Mathematics; Set (abstract data type); Population; Mink; Statistical hypothesis testing; Statistics; Differential equation; Mathematical analysis; Computer science; Ecology; Biology","score_opus":0.07090110817239888,"score_gpt":0.3703196940783881,"score_spread":0.29941858590598924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024653850","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":[0.6585974,0.000035514244,0.13512321,0.0016291009,0.00033809067,0.0004035481,0.00001787934,0.00011396325,0.20374128],"genre_scores_gemma":[0.9806226,0.0000015523915,0.018119726,0.0010112827,0.00006504584,0.000007632915,0.000025055851,0.0000072147072,0.0001398768],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9990367,0.000049832834,0.0003634985,0.00018007452,0.00007622638,0.00029365596],"domain_scores_gemma":[0.99761724,0.0020588432,0.00003301488,0.00009818094,0.000024035176,0.00016867566],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006322958,0.00008584267,0.0002376567,0.0000595123,0.000052271655,0.0000030978856,0.000030678617,0.00012089978,0.0009611742],"category_scores_gemma":[0.0052486975,0.000066576446,0.000028921422,0.000098119664,0.00018493812,0.00004576217,0.00001925997,0.00028533666,0.000111006055],"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":[0.0001432914,0.0001362727,0.032752715,0.00004302614,0.000010598935,0.000060521994,0.000039301653,0.000018231607,0.00038807202,0.96087885,0.00009071185,0.0054384037],"study_design_scores_gemma":[0.0005401224,0.000206331,0.4940181,0.00007241641,0.00004286429,0.000048842627,0.00008137643,0.012398173,0.000034002896,0.49229732,0.00015531968,0.000105128114],"about_ca_topic_score_codex":0.000020481239,"about_ca_topic_score_gemma":0.00005088236,"teacher_disagreement_score":0.46858156,"about_ca_system_score_codex":0.00004420742,"about_ca_system_score_gemma":0.000019075844,"threshold_uncertainty_score":0.9999521},"labels":[],"label_agreement":null},{"id":"W2025425088","doi":"10.1007/s00362-010-0344-3","title":"Pseudolikelihood ratio test with biased observations","year":2010,"lang":"en","type":"article","venue":"Statistical Papers","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":"Simon Fraser University","funders":"","keywords":"Null hypothesis; Construct (python library); Null (SQL); Statistics; Test (biology); Statistical hypothesis testing; Mathematics; Association (psychology); Alternative hypothesis; Sample size determination; Computer science; Econometrics; Psychology; Data mining; Biology","score_opus":0.05115523037100574,"score_gpt":0.3385866532938162,"score_spread":0.2874314229228105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025425088","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":[0.0037828244,0.00000145292,0.97063434,0.00065923645,0.00016966467,0.0002688716,0.00049073837,0.00014123267,0.023851631],"genre_scores_gemma":[0.20614299,0.0000010858972,0.79311883,0.00029130056,0.00008817176,0.00004279976,0.000026238275,0.000028732571,0.00025982683],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99858135,0.00007114801,0.00032623435,0.00032756748,0.00033411404,0.00035960245],"domain_scores_gemma":[0.9910258,0.008131915,0.00007846364,0.00036490738,0.0001367632,0.0002621706],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00025379707,0.00020582764,0.0002746854,0.00004231273,0.00017659024,0.000079703095,0.00017353681,0.00009612957,0.0023223076],"category_scores_gemma":[0.011256462,0.00014988799,0.000032466385,0.00022732216,0.000334211,0.00006869873,0.000026902084,0.00043277882,0.00007350866],"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":[0.000018211173,0.00014551356,0.002250317,0.00003735309,0.000016237896,0.000027446118,0.000060629816,1.1936572e-7,0.010508322,0.9732244,0.002080531,0.011630897],"study_design_scores_gemma":[0.0006755815,0.00030778948,0.050525956,0.00003477444,0.000099786484,0.000026087844,0.000092081915,0.0009351081,0.0004630052,0.94390625,0.0025460771,0.000387497],"about_ca_topic_score_codex":0.000026635507,"about_ca_topic_score_gemma":0.00019765968,"teacher_disagreement_score":0.20236017,"about_ca_system_score_codex":0.000015933065,"about_ca_system_score_gemma":0.00012402536,"threshold_uncertainty_score":0.9985897},"labels":[],"label_agreement":null},{"id":"W2026759268","doi":"10.1007/s00362-009-0237-5","title":"Empirical likelihood for density-weighted average derivatives","year":2009,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Methods and Inference","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":"University of Calgary","funders":"Natural Science Foundation of Hunan Province; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Empirical likelihood; Mathematics; Statistics; Inference; Monte Carlo method; Nonparametric statistics; Statistical inference; Density estimation; Applied mathematics; Confidence interval; Computer science; Estimator","score_opus":0.06903304803505796,"score_gpt":0.39434868396494865,"score_spread":0.3253156359298907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026759268","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":[0.008847295,0.000013849707,0.9715418,0.0010261713,0.00012361202,0.0004029093,0.00024024592,0.00013038059,0.017673686],"genre_scores_gemma":[0.33877805,0.0000044121866,0.65966606,0.0012495689,0.000088329216,0.00002057771,0.000021185953,0.00001850356,0.00015334686],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981585,0.00017075086,0.00042163543,0.00041495325,0.00029217728,0.0005419953],"domain_scores_gemma":[0.9927009,0.0065339524,0.00007664413,0.0002549493,0.0001325517,0.00030100753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035798113,0.00024370482,0.00043528774,0.00004769312,0.00017156797,0.000052358184,0.00016495275,0.00012129277,0.00072818116],"category_scores_gemma":[0.007464171,0.0001962708,0.00008785094,0.00014681612,0.00016961481,0.00004306432,0.000027770982,0.00021720337,0.000036530364],"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":[0.00010783045,0.00018657722,0.00019233597,0.000048140344,0.000029769157,0.000021999238,0.00022373076,1.7000339e-7,0.0015223483,0.9079203,0.0074965227,0.082250305],"study_design_scores_gemma":[0.00060891383,0.0005693066,0.01671331,0.00002828312,0.000054762095,0.00000615584,0.000058409383,0.0013878535,0.000613081,0.97676915,0.0028921238,0.00029865984],"about_ca_topic_score_codex":0.000002974344,"about_ca_topic_score_gemma":0.0000040638856,"teacher_disagreement_score":0.32993075,"about_ca_system_score_codex":0.00004889144,"about_ca_system_score_gemma":0.00006477782,"threshold_uncertainty_score":0.8935849},"labels":[],"label_agreement":null},{"id":"W2030360389","doi":"10.1007/s00362-010-0343-4","title":"Robust second-order least-squares estimator for regression models","year":2010,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Advanced Statistical Methods and Models","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":"University of Victoria","funders":"","keywords":"Estimator; Robust regression; Outlier; Ordinary least squares; Mathematics; Least trimmed squares; Robustness (evolution); Robust statistics; Non-linear least squares; Applied mathematics; Generalized least squares; Moment (physics); Least-squares function approximation; Nonlinear regression; Statistics; Regression analysis","score_opus":0.12626239176167273,"score_gpt":0.4167130343025888,"score_spread":0.2904506425409161,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030360389","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":[0.0008087658,0.000016234391,0.98218966,0.00023024718,0.00042514066,0.0005479094,0.0010567509,0.00013675327,0.0145885665],"genre_scores_gemma":[0.051479112,0.0000030575443,0.9463763,0.00017845408,0.00013011762,0.0001459693,0.000048271846,0.00007576977,0.001562926],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980618,0.00007531943,0.00045378527,0.000533998,0.0003119671,0.0005631707],"domain_scores_gemma":[0.99418366,0.0047385115,0.00011297422,0.0004031093,0.00019935722,0.00036240343],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000392602,0.0003040618,0.0004578434,0.000050190367,0.0002607005,0.000048670525,0.00020025606,0.00019173583,0.001587659],"category_scores_gemma":[0.0055384194,0.00023342151,0.00008502229,0.00009298134,0.00027515527,0.0001447572,0.000060343653,0.0004502472,0.000018157854],"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":[0.000107948705,0.00009323574,0.0000035531575,0.00018961269,0.000021650716,0.000010505974,0.00008508511,0.00024697027,0.0036216401,0.9552923,0.00468958,0.03563796],"study_design_scores_gemma":[0.0006553813,0.000119875964,0.000029746881,0.000037426136,0.00005521795,0.000008879179,0.00009219777,0.107541904,0.00021175134,0.88616246,0.0047679036,0.00031723734],"about_ca_topic_score_codex":0.0000057017414,"about_ca_topic_score_gemma":0.00007456067,"teacher_disagreement_score":0.10729493,"about_ca_system_score_codex":0.000026095197,"about_ca_system_score_gemma":0.00008086312,"threshold_uncertainty_score":0.99932504},"labels":[],"label_agreement":null},{"id":"W2031364987","doi":"10.1007/s00362-008-0165-9","title":"Inference on effect size indices from several two-armed experiments","year":2008,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Methods in Clinical Trials","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":"University of Windsor","funders":"","keywords":"Bootstrapping (finance); Estimator; Statistics; Mathematics; Bivariate analysis; Sample size determination; Confidence interval; Inference; Null hypothesis; Statistical hypothesis testing; Homogeneity (statistics); Monte Carlo method; Series (stratigraphy); Computer science; Econometrics; Artificial intelligence","score_opus":0.3938085268102587,"score_gpt":0.5614108691675798,"score_spread":0.16760234235732108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031364987","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":[0.7314113,0.000048294503,0.16241644,0.0003746408,0.0031393091,0.0021715674,0.0028005948,0.000730861,0.096907035],"genre_scores_gemma":[0.5623484,0.00001067203,0.43653637,0.00055527734,0.0002259925,0.00006994272,0.000010672153,0.00004016574,0.00020250295],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9953371,0.0015325194,0.0008936653,0.0007280345,0.0009126756,0.0005959492],"domain_scores_gemma":[0.7973142,0.20163836,0.00017760944,0.00045525117,0.000044344033,0.0003702109],"candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000925707,0.00041488354,0.0009657219,0.000045845165,0.00021226381,0.000041921674,0.00038184854,0.0002042068,0.0061393487],"category_scores_gemma":[0.17674592,0.0003255316,0.00013738358,0.00016761007,0.00066286104,0.00006018755,0.00012405362,0.000572597,0.00053011783],"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":[0.006079083,0.002568324,0.016548147,0.0003705642,0.0013018999,0.0022519247,0.0027366031,0.00003667503,0.012028535,0.84443104,0.026764223,0.08488299],"study_design_scores_gemma":[0.0055990806,0.0015421187,0.030910168,0.0001685556,0.00018124074,0.0000073019214,0.00006140242,0.00029806505,0.0040614232,0.9558071,0.0005892318,0.00077435176],"about_ca_topic_score_codex":0.000106034655,"about_ca_topic_score_gemma":0.000007336223,"teacher_disagreement_score":0.2741199,"about_ca_system_score_codex":0.00010518139,"about_ca_system_score_gemma":0.000082437014,"threshold_uncertainty_score":0.99991965},"labels":[],"label_agreement":null},{"id":"W2032307119","doi":"10.1007/s00362-010-0319-4","title":"Erratum to: Exact expression of the density of the sample generalized variance and applications","year":2010,"lang":"en","type":"erratum","venue":"Statistical Papers","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":"Université de Moncton","funders":"","keywords":"Variance (accounting); Expression (computer science); Sample (material); Statistics; Econometrics; Mathematics; Computer science; Chemistry; Economics; Chromatography","score_opus":0.0441503101617369,"score_gpt":0.3691024975700473,"score_spread":0.32495218740831044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032307119","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":[0.00007829202,0.000045539247,0.984276,0.00021743811,0.0021043832,0.0009649581,0.0031461928,0.000016843105,0.009150347],"genre_scores_gemma":[0.004818885,0.000054554574,0.98236233,0.00024316242,0.00026234018,0.00014161474,0.000046203557,0.000062988605,0.012007932],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979777,0.00029954605,0.0005504589,0.00042634868,0.0004722498,0.00027374536],"domain_scores_gemma":[0.9949552,0.0033763524,0.00038733723,0.00095812115,0.00016677691,0.0001562484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032201887,0.00027593516,0.00063092215,0.000025909403,0.00020414787,0.000014424531,0.0004631468,0.0003421397,0.00012311384],"category_scores_gemma":[0.006687018,0.00015468845,0.00011127527,0.00017033154,0.0005759967,0.000020965223,0.0003430899,0.0009308285,9.38282e-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":[0.000044670578,0.00009571887,0.00003338031,0.00059340906,0.000034435427,7.2683656e-7,0.00016630422,0.000006995063,0.01728049,0.8301876,0.14463612,0.006920099],"study_design_scores_gemma":[0.00021801416,0.00003651211,0.0016084455,0.00024189384,0.00017465882,0.000002592075,0.000029068142,0.00015891729,0.0011411416,0.92390776,0.072250634,0.00023035571],"about_ca_topic_score_codex":0.00007387478,"about_ca_topic_score_gemma":0.00013567488,"teacher_disagreement_score":0.093720116,"about_ca_system_score_codex":0.000027746253,"about_ca_system_score_gemma":0.00015823092,"threshold_uncertainty_score":0.8005469},"labels":[],"label_agreement":null},{"id":"W2035858701","doi":"10.1007/s00362-011-0383-4","title":"Outer and inner prediction intervals for order statistics intervals based on current records","year":2011,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","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":"McMaster University","funders":"","keywords":"Statistics; Mathematics; Sequence (biology); Order statistic; Interval (graph theory); Range (aeronautics); Sample (material); Prediction interval; Sample size determination; Distribution (mathematics); Confidence interval; Combinatorics; Physics; Mathematical analysis","score_opus":0.10784033655159313,"score_gpt":0.3735777653273165,"score_spread":0.26573742877572337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035858701","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":[0.00024216107,0.0000060839775,0.9794378,0.0002286728,0.000274522,0.0006344969,0.013061592,0.000114269686,0.0060003716],"genre_scores_gemma":[0.36605686,0.0000120187005,0.63097924,0.00070006604,0.00008750109,0.0005657092,0.0012161392,0.0000559908,0.00032648668],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99843353,0.00009221069,0.00054841227,0.00038751462,0.00024432645,0.0002940212],"domain_scores_gemma":[0.99718195,0.0019526252,0.0001258812,0.00025287856,0.00025608312,0.00023058348],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00028559478,0.00022419178,0.0002723488,0.000074184056,0.0001430502,0.000044610322,0.000110547415,0.000081067315,0.0020740267],"category_scores_gemma":[0.0036347974,0.00019449621,0.0000445459,0.00012774384,0.00022933725,0.00005404037,0.00003120232,0.00018041278,0.00006431593],"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":[0.00011707565,0.00031214146,0.00016911048,0.0001757344,0.000019237668,0.000001749029,0.00012671498,0.0000023058121,0.000020900232,0.915356,0.037023798,0.046675254],"study_design_scores_gemma":[0.0021671595,0.0009267146,0.023764534,0.00021610758,0.00027803547,0.000005134414,0.00012868353,0.12894368,0.00013875258,0.82238805,0.020462926,0.0005802373],"about_ca_topic_score_codex":0.000008351787,"about_ca_topic_score_gemma":0.000012371486,"teacher_disagreement_score":0.3658147,"about_ca_system_score_codex":0.000069278336,"about_ca_system_score_gemma":0.000050080875,"threshold_uncertainty_score":0.9988382},"labels":[],"label_agreement":null},{"id":"W2039834917","doi":"10.1007/s00362-007-0358-z","title":"Some preservation results of NBUC aging property with applications","year":2007,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Markov Chains and Monte Carlo Methods","field":"Mathematics","cited_by":6,"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":"AGE-WELL; Alberta Agricultural Research Institute","keywords":"Property (philosophy); Computer science; Philosophy; Epistemology","score_opus":0.054320659771558595,"score_gpt":0.35623083686800067,"score_spread":0.3019101770964421,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039834917","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":[0.0025863554,0.00003400259,0.9003016,0.00036357137,0.000041439922,0.00070345605,0.00014533276,0.00007261172,0.095751666],"genre_scores_gemma":[0.22212097,0.000013738383,0.77286416,0.00012706184,0.00014887442,0.000059113525,0.000047179572,0.000030498577,0.0045883795],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99891526,0.00005758742,0.0003547192,0.00020518311,0.00025705362,0.00021017996],"domain_scores_gemma":[0.9981357,0.0012549199,0.00011850227,0.0002815763,0.00011272005,0.00009658046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009334107,0.00010287211,0.00018216575,0.0000439993,0.00005885614,0.000009803883,0.00010026456,0.000047341357,0.000014198429],"category_scores_gemma":[0.000847873,0.00006209885,0.00002537821,0.0001375133,0.00012607536,0.000068859175,0.000027871121,0.00010806653,1.7943046e-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":[0.00038159033,0.00015866804,0.00019066407,0.00033239307,0.00004359112,0.000010674846,0.0005419789,0.000007860531,0.008406902,0.93252695,0.0023653354,0.05503341],"study_design_scores_gemma":[0.013069579,0.0021240043,0.009785321,0.00082056253,0.00073131965,0.000046826313,0.005096482,0.003830077,0.030025097,0.4345689,0.49758378,0.0023180454],"about_ca_topic_score_codex":0.000049712067,"about_ca_topic_score_gemma":0.00010205824,"teacher_disagreement_score":0.49795803,"about_ca_system_score_codex":0.00003132823,"about_ca_system_score_gemma":0.000036585603,"threshold_uncertainty_score":0.25323176},"labels":[],"label_agreement":null},{"id":"W2057396628","doi":"10.1007/s00362-012-0430-9","title":"On the exact joint distribution of a linear combination of order statistics and their concomitants in an exchangeable multivariate normal distribution","year":2012,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":6,"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":"Centre de Recherches Mathématiques","keywords":"Multivariate statistics; Mathematics; Statistics; Joint probability distribution; Multivariate normal distribution; Skew normal distribution; Order statistic; Distribution (mathematics); Joint (building); Multivariate analysis; Normal distribution; Applied mathematics; Mathematical analysis; Engineering","score_opus":0.06476238031241036,"score_gpt":0.340057786652715,"score_spread":0.2752954063403047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057396628","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":[0.15315187,0.000009048371,0.82947785,0.00017714863,0.000046832778,0.00042907204,0.016379297,0.000021240676,0.00030762202],"genre_scores_gemma":[0.98903215,0.0000071334084,0.0081702415,0.00003767063,0.000015079015,0.000054403128,0.0026571222,0.000013365606,0.000012807507],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99842465,0.0002506769,0.00059212133,0.00018025716,0.00025932267,0.00029294466],"domain_scores_gemma":[0.99625105,0.0028819002,0.00024689912,0.00022834468,0.00024434418,0.000147459],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063173746,0.00017651258,0.00031128357,0.000034024808,0.00012386209,0.0000140344255,0.00009131408,0.00008812514,0.00034545525],"category_scores_gemma":[0.00420336,0.00012607005,0.000025570242,0.00026966486,0.00034341036,0.00011248333,0.0000365795,0.00018339652,0.00000787542],"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":[0.00006528319,0.0006301582,0.0006890333,0.00008172713,0.000015242036,3.896904e-7,0.00032947512,0.000014576936,0.0010368981,0.99448985,0.0005423918,0.002104968],"study_design_scores_gemma":[0.00245997,0.00054254296,0.5400149,0.00016371046,0.000106973304,0.0000055416917,0.001692786,0.10547907,0.0031592331,0.34566647,0.00024811618,0.0004606768],"about_ca_topic_score_codex":0.000065231274,"about_ca_topic_score_gemma":0.000020948628,"teacher_disagreement_score":0.83588034,"about_ca_system_score_codex":0.000090428985,"about_ca_system_score_gemma":0.00004009112,"threshold_uncertainty_score":0.51409876},"labels":[],"label_agreement":null},{"id":"W2062757447","doi":"10.1007/s00362-009-0261-5","title":"Some comments on Latin squares and on Graeco-Latin squares, illustrated with postage stamps and old playing cards","year":2009,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Cultural Heritage Materials Analysis","field":"Arts and Humanities","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":"Dawson College; McGill University","funders":"Dartmouth College","keywords":"Postage Stamps; Latin square; Art; Art history; Chemistry","score_opus":0.025947668668076115,"score_gpt":0.24026932336951354,"score_spread":0.21432165470143744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062757447","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":[0.9815477,0.000056819426,0.000004664194,0.00063440803,0.00006994596,0.00023190746,0.00095960894,0.000070115304,0.016424803],"genre_scores_gemma":[0.99639785,0.00001877406,0.00019510907,0.0011053162,0.000119983415,0.0000062274066,0.00018793074,0.00001893928,0.0019498967],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9987724,0.00008077905,0.00024784863,0.00032741815,0.00027755677,0.00029403175],"domain_scores_gemma":[0.99941427,0.00019420522,0.000070080634,0.00013398388,0.00004340635,0.00014408125],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008474493,0.0002500104,0.00031696886,0.00008699772,0.0003974294,0.00036752372,0.000058712554,0.000047275855,0.0010785842],"category_scores_gemma":[0.000046873287,0.00017124788,0.000025378928,0.00004598869,0.00025125424,0.00010918281,0.000018404437,0.00015023637,0.000012589946],"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":[0.0007277025,0.00017575061,0.0013866827,0.000110057015,0.00017009486,0.00016316914,0.009333866,0.00004133835,0.0034586263,0.9720112,0.0020144666,0.010407014],"study_design_scores_gemma":[0.015978131,0.029481227,0.7567,0.0019264168,0.0016387742,0.000029570987,0.05749685,0.0030329288,0.0011046956,0.037592396,0.08884866,0.0061703464],"about_ca_topic_score_codex":0.00056338916,"about_ca_topic_score_gemma":0.0007865895,"teacher_disagreement_score":0.93441886,"about_ca_system_score_codex":0.00004041916,"about_ca_system_score_gemma":0.000009503307,"threshold_uncertainty_score":0.99983454},"labels":[],"label_agreement":null},{"id":"W2068480341","doi":"10.1007/s00362-013-0569-z","title":"Analyzing supersaturated designs for discrete responses via generalized linear models","year":2013,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Optimal Experimental Design Methods","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":"McMaster University","funders":"National Technical University of Athens","keywords":"Factorial experiment; Design of experiments; Supersaturation; Computer science; Identification (biology); Optimal design; Linear regression; Factorial; Mathematical optimization; Discrete time and continuous time; Mathematics; Statistics","score_opus":0.19680439901753044,"score_gpt":0.4569285278511817,"score_spread":0.26012412883365127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068480341","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":[0.016041046,0.000113071415,0.9785831,0.00049169327,0.00022194938,0.00080772187,0.00023665883,0.000082775434,0.0034220077],"genre_scores_gemma":[0.41456217,0.000005122047,0.5831292,0.00028016078,0.000050053626,0.00011419917,0.000028434128,0.000029045108,0.0018015798],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9958349,0.0011134745,0.0008042531,0.0007860075,0.00086238567,0.0005990176],"domain_scores_gemma":[0.9899132,0.00866436,0.00012593115,0.00052107195,0.00036592822,0.0004094837],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002160614,0.0002851728,0.00051432813,0.0002008278,0.00027405858,0.00035182908,0.0005701294,0.00012984408,0.0029620554],"category_scores_gemma":[0.0068563027,0.00020180494,0.00017519413,0.0005463364,0.0003507511,0.00052141957,0.000098937264,0.00016575296,0.00037444071],"study_design_candidate":"bench_or_experimental","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":[0.0011443006,0.000083367355,0.0002452779,0.000011996257,0.00010707744,0.000020692112,0.0006700975,0.0037652133,0.8790966,0.059567682,0.009292902,0.04599479],"study_design_scores_gemma":[0.0012417185,0.00050143857,0.001254504,0.000012763255,0.000055066535,0.0000082785855,0.0009023365,0.78064066,0.012342226,0.20093976,0.0015491477,0.0005520947],"about_ca_topic_score_codex":0.00020948541,"about_ca_topic_score_gemma":0.0000072689836,"teacher_disagreement_score":0.86675435,"about_ca_system_score_codex":0.00008076627,"about_ca_system_score_gemma":0.00009412835,"threshold_uncertainty_score":0.99794936},"labels":[],"label_agreement":null},{"id":"W2078254747","doi":"10.1007/s00362-011-0376-3","title":"Unbiased and almost unbiased ratio estimators of the population mean in ranked set sampling","year":2011,"lang":"en","type":"article","venue":"Statistical Papers","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":"Université de Montréal; University of Manitoba","funders":"","keywords":"RSS; Estimator; Statistics; Mean squared error; Bias of an estimator; Mathematics; Simple random sample; Efficiency; Best linear unbiased prediction; Population; Efficient estimator; Ratio estimator; U-statistic; Stein's unbiased risk estimate; Minimum-variance unbiased estimator; Computer science; Artificial intelligence; Demography","score_opus":0.13860332041301862,"score_gpt":0.3659429681020982,"score_spread":0.22733964768907958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078254747","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":[0.2016733,0.000010114608,0.7911125,0.00028688103,0.00009328906,0.00085638475,0.0015547248,0.00008262495,0.0043301717],"genre_scores_gemma":[0.9415061,0.0000016026638,0.058167707,0.0000866228,0.000006461798,0.00003199812,0.00016618917,0.000013639479,0.000019713836],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9987193,0.0001221292,0.0005135793,0.0002224752,0.00023133248,0.00019120023],"domain_scores_gemma":[0.9981784,0.0012676006,0.00014355818,0.0002425398,0.00006163229,0.00010621879],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025806588,0.00013636811,0.00022728318,0.000045888206,0.000113046204,0.000015147181,0.00011105173,0.0000660424,0.00058693194],"category_scores_gemma":[0.0024489472,0.00010631322,0.00003389746,0.0002713936,0.0002542824,0.000048585694,0.000032434844,0.00013228576,0.000007986191],"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":[0.00003061011,0.00008352119,0.0055802544,0.00006139869,0.000013223971,0.0000010952753,0.00046177657,0.000015720992,0.00032376315,0.9916497,0.00015945159,0.0016194676],"study_design_scores_gemma":[0.00093663146,0.000034987082,0.66489774,0.00007841798,0.00007679092,0.0000038598637,0.00036064984,0.013683333,0.00031912196,0.3193405,0.000059283222,0.00020867841],"about_ca_topic_score_codex":0.00025587695,"about_ca_topic_score_gemma":0.00020197625,"teacher_disagreement_score":0.73983276,"about_ca_system_score_codex":0.000049124155,"about_ca_system_score_gemma":0.00003415224,"threshold_uncertainty_score":0.64264935},"labels":[],"label_agreement":null},{"id":"W2082120092","doi":"10.1007/s003620100067","title":"Estimation of mean and variance of stigmatized quantitative variable using distinct units in randomized response sampling","year":2001,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Survey Sampling and Estimation Techniques","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":"University of Windsor","funders":"","keywords":"Randomized response; Statistics; Variance (accounting); Estimation; Econometrics; Mathematics; Estimator; Economics","score_opus":0.13691295140119766,"score_gpt":0.40082266029477076,"score_spread":0.2639097088935731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082120092","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":[0.31258667,0.00002598128,0.68666553,0.00001302286,0.000020912707,0.00026633794,0.00007506611,0.000033731416,0.0003127641],"genre_scores_gemma":[0.5422368,0.000007698317,0.45771182,0.0000036631473,0.0000018474303,0.00000884001,0.000011536497,0.000009850409,0.000007905186],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99770445,0.0009512446,0.0007702995,0.00018707065,0.00021957055,0.00016735056],"domain_scores_gemma":[0.9765627,0.02275331,0.0003147851,0.00015615251,0.00015915098,0.000053903186],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0042781257,0.00013993403,0.0007154565,0.00015887956,0.000051443236,0.000013736531,0.000070038914,0.00007733663,0.00006728538],"category_scores_gemma":[0.041386507,0.00012551149,0.000027811857,0.00040943484,0.00026293762,0.00007640243,0.000026898559,0.00011701052,4.774669e-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":[0.084599525,0.0002648484,0.00079947326,0.0009833588,0.00015308996,0.000011612489,0.005087715,0.0096594095,0.013212303,0.87514806,0.000023377686,0.010057224],"study_design_scores_gemma":[0.019238217,0.00012179676,0.002843972,0.00081041927,0.00012517702,0.000009854592,0.0005065925,0.5705558,0.0006099406,0.4049296,0.0000067099613,0.00024190573],"about_ca_topic_score_codex":0.0005248385,"about_ca_topic_score_gemma":0.000047714628,"teacher_disagreement_score":0.5608964,"about_ca_system_score_codex":0.000041565916,"about_ca_system_score_gemma":0.000094445124,"threshold_uncertainty_score":0.9666883},"labels":[],"label_agreement":null},{"id":"W2088606685","doi":"10.1007/s00362-006-0032-5","title":"On the natural restrictions in the singular Gauss–Markov model","year":2006,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Markov Chains and Monte Carlo Methods","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 Alberta","funders":"","keywords":"Natural (archaeology); Gauss; Markov chain; Markov model; Econometrics; Mathematical economics; Mathematics; Applied mathematics; Computer science; Statistical physics; Statistics; Geography; Physics","score_opus":0.036227202114213604,"score_gpt":0.32963675568475,"score_spread":0.2934095535705364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088606685","genre_codex":"other","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":[0.11333621,0.00014720816,0.20159279,0.009912614,0.00051950885,0.001194477,0.0001786049,0.00013458516,0.672984],"genre_scores_gemma":[0.93769217,0.000005791816,0.05957335,0.0010034902,0.000076628785,0.000043606433,0.0000114666955,0.000018692293,0.0015747934],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986567,0.00034111386,0.00023458443,0.0001884705,0.0003135298,0.00026560054],"domain_scores_gemma":[0.9946595,0.0048986124,0.00004216472,0.00034176864,0.000026503703,0.000031467585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007503752,0.00013630932,0.00014275947,0.000039549966,0.00017841498,0.000045017372,0.0001999939,0.00005503503,0.00003747204],"category_scores_gemma":[0.0018707465,0.00006951211,0.0000611418,0.00017897146,0.00013116683,0.00001934026,0.00002421347,0.00038086646,5.507811e-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":[0.000019942296,0.00007145713,0.000017118542,0.000009586121,0.0000058076503,0.000019539122,0.00015670805,0.00010244328,0.00020740894,0.96894103,0.028686712,0.0017622644],"study_design_scores_gemma":[0.00049036555,0.00008229948,0.0012307152,0.000041624953,0.000060386174,0.000011696028,0.0007787783,0.07999537,0.000030386778,0.9121666,0.004832915,0.00027886158],"about_ca_topic_score_codex":0.00012868902,"about_ca_topic_score_gemma":0.0003269468,"teacher_disagreement_score":0.82435596,"about_ca_system_score_codex":0.000052076608,"about_ca_system_score_gemma":0.00003277205,"threshold_uncertainty_score":0.28346217},"labels":[],"label_agreement":null},{"id":"W2091466376","doi":"10.1007/s00362-011-0365-6","title":"Discrete approximations of continuous and mixed measures on a compact interval","year":2011,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":21,"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":"Ryerson University","keywords":"Nonparametric statistics; Discretization; Interval (graph theory); Mathematics; Parametric statistics; Measure (data warehouse); Applied mathematics; Zero (linguistics); Goodness of fit; Statistics; Computer science; Mathematical analysis; Combinatorics; Data mining","score_opus":0.13054802111633892,"score_gpt":0.3596558829496474,"score_spread":0.22910786183330847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091466376","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":[0.045488823,0.000021162046,0.7822444,0.00010375982,0.00015232294,0.00037756085,0.0007490885,0.00007022428,0.1707927],"genre_scores_gemma":[0.71913356,0.0000027847648,0.28075072,0.000035041645,0.000008561636,0.000005484616,0.000003525917,0.000010621388,0.000049681425],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989239,0.0001749118,0.0003237237,0.00018576349,0.00020497071,0.00018671907],"domain_scores_gemma":[0.99723625,0.0023095272,0.000085566724,0.0001708785,0.00005944022,0.00013831706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028308158,0.0001331013,0.00034018236,0.000037793154,0.000046261892,0.000012629416,0.000089280424,0.000046270918,0.00054938864],"category_scores_gemma":[0.0043795705,0.00009841889,0.00003638239,0.000057085734,0.00037168834,0.000021906892,0.000024977484,0.00013215198,0.000008870735],"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":[0.000091179856,0.00010123914,0.00040556927,0.00007648006,0.000039326602,0.000005474106,0.0005966504,8.151205e-8,0.00045309446,0.96928036,0.0005510042,0.028399535],"study_design_scores_gemma":[0.00053243054,0.00079688453,0.052453116,0.00012724208,0.000104275605,0.000006260383,0.0006175343,0.00060369296,0.0011875753,0.94314426,0.00019939551,0.0002273458],"about_ca_topic_score_codex":0.00005581855,"about_ca_topic_score_gemma":0.000013324483,"teacher_disagreement_score":0.6736448,"about_ca_system_score_codex":0.000011598481,"about_ca_system_score_gemma":0.000016458232,"threshold_uncertainty_score":0.60154206},"labels":[],"label_agreement":null},{"id":"W2091880980","doi":"10.1007/s00362-008-0132-5","title":"On generalized semi-Pareto and semi-Burr distributions and random coefficient minification processes","year":2008,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","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":"Dalhousie University","funders":"","keywords":"Lomax distribution; Pareto principle; Pareto interpolation; Mathematics; Generalization; Pareto distribution; Autoregressive model; Applied mathematics; Generalized Pareto distribution; Class (philosophy); Marginal distribution; Distribution (mathematics); Mathematical optimization; Statistics; Random variable; Computer science; Mathematical analysis; Extreme value theory; Artificial intelligence","score_opus":0.04387240503557042,"score_gpt":0.3291155020448698,"score_spread":0.28524309700929934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091880980","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":[0.049768675,0.00006663713,0.941283,0.00092000543,0.000038663282,0.000551751,0.003298068,0.00014314757,0.003930077],"genre_scores_gemma":[0.98737115,0.00011423054,0.011122062,0.00018784571,0.000023752418,0.00016817509,0.0007397705,0.00001694113,0.0002560921],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986159,0.000077195145,0.0003823696,0.00038166466,0.0002890908,0.00025375825],"domain_scores_gemma":[0.9967169,0.0025588097,0.000093838134,0.000199735,0.00015818232,0.0002725016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001355065,0.00019521864,0.000264419,0.000042622567,0.00047665185,0.00004506496,0.00007225934,0.000078244084,0.00034337552],"category_scores_gemma":[0.004435422,0.00017070101,0.000024372895,0.0002341618,0.000535951,0.000043672397,0.00002790469,0.00013172583,0.00003814781],"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":[0.00006337653,0.00018043122,0.000082353436,0.000099038516,0.000017261966,0.0000056938866,0.00012348042,0.000011355417,0.00028621507,0.9873022,0.011094523,0.0007340801],"study_design_scores_gemma":[0.01287642,0.0006424205,0.08687972,0.00030314975,0.00061118003,0.00041222965,0.00077871425,0.05657744,0.0017531111,0.8132065,0.023848161,0.0021109704],"about_ca_topic_score_codex":0.000008609354,"about_ca_topic_score_gemma":0.0000070985666,"teacher_disagreement_score":0.93760246,"about_ca_system_score_codex":0.00005346716,"about_ca_system_score_gemma":0.000074585434,"threshold_uncertainty_score":0.6960985},"labels":[],"label_agreement":null},{"id":"W2093639777","doi":"10.1007/s00362-006-0034-3","title":"A note on inference for P(X  <  Y) for right truncated exponentially distributed data","year":2006,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","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":"York University","funders":"","keywords":"Inference; Reliability (semiconductor); Monte Carlo method; Confidence interval; Mathematics; Applied mathematics; Statistics; Exponential growth; Maximum likelihood; Statistical inference; Exponential distribution; Algorithm; Computer science; Mathematical analysis; Physics; Artificial intelligence; Quantum mechanics","score_opus":0.079884625652137,"score_gpt":0.39658039850057586,"score_spread":0.31669577284843886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093639777","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":[0.00013800873,0.0000026807872,0.91177934,0.0010062313,0.00008234156,0.0010086661,0.08311341,0.0001507214,0.0027185914],"genre_scores_gemma":[0.6322225,0.0000013536353,0.32034528,0.00022220802,0.00012599552,0.0006119587,0.046035375,0.000038671318,0.00039669083],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99829024,0.000039256523,0.0005201319,0.0005028153,0.00026671292,0.00038083427],"domain_scores_gemma":[0.9928213,0.0061204094,0.00013060444,0.0005787743,0.00020111806,0.00014782221],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022639279,0.00021049423,0.0002757803,0.000038295715,0.0002738146,0.00007451775,0.0003479959,0.00009909235,0.0005791787],"category_scores_gemma":[0.0061638667,0.0001861395,0.000057930287,0.00016084553,0.00017525944,0.000064926804,0.000049490514,0.00009857496,0.00006366392],"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":[0.0001032298,0.00025502834,0.000003189485,0.00006884728,0.00001624694,0.0000012708135,0.000005396102,0.000020411839,0.0007293989,0.9159058,0.08059643,0.0022947802],"study_design_scores_gemma":[0.0017688376,0.0001560727,0.0025066584,0.00003215813,0.000160605,0.0000014121673,0.000011430634,0.08258491,0.00030619447,0.82564366,0.086470045,0.00035801105],"about_ca_topic_score_codex":0.000015928987,"about_ca_topic_score_gemma":0.000061589926,"teacher_disagreement_score":0.6320844,"about_ca_system_score_codex":0.000077729834,"about_ca_system_score_gemma":0.00009314818,"threshold_uncertainty_score":0.7590549},"labels":[],"label_agreement":null},{"id":"W2094500625","doi":"10.1007/bf02925763","title":"On the sampling performance of an inequality pre-test estimator of the regression error variance under LINEX loss","year":2000,"lang":"en","type":"article","venue":"Statistical Papers","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":"Western University","funders":"University of Hong Kong","keywords":"Estimator; Mean squared error; Mathematics; Statistics; Constraint (computer-aided design); Variance (accounting); Minimum-variance unbiased estimator; Bias of an estimator; Efficient estimator; Regression analysis; Inequality; Econometrics; Economics","score_opus":0.12083337249804006,"score_gpt":0.4382807125006209,"score_spread":0.31744734000258085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094500625","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":[0.38238153,0.000009020836,0.61402446,0.00035600245,0.00007331578,0.00036528206,0.00052960066,0.000027486687,0.0022332727],"genre_scores_gemma":[0.672072,0.0000070219876,0.32755372,0.00012935529,0.000019158791,0.000012195035,0.0000042281004,0.000017863174,0.00018446714],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982359,0.0002850865,0.0005233629,0.0002693729,0.00043150457,0.00025477872],"domain_scores_gemma":[0.990181,0.0088683795,0.00018966873,0.00058764056,0.00007730158,0.00009596533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063462084,0.00018472134,0.00033780315,0.0000130901835,0.00017407954,0.000009864766,0.0002974443,0.000077601144,0.00085495703],"category_scores_gemma":[0.004622556,0.00009303744,0.00005548748,0.0001327849,0.00047626006,0.000061136714,0.000044868586,0.00028334794,0.0000041987555],"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":[0.0002848739,0.00033739387,0.00013209048,0.00026074733,0.000019514642,0.0000018179043,0.00023486755,0.0029570488,0.0017680625,0.9652662,0.0000752538,0.028662104],"study_design_scores_gemma":[0.00042089145,0.0004256623,0.013268937,0.00042923592,0.00006762119,0.0000044111594,0.000084549916,0.070909075,0.0014969789,0.91257447,0.000105740946,0.00021244677],"about_ca_topic_score_codex":0.000012763499,"about_ca_topic_score_gemma":0.000006366186,"teacher_disagreement_score":0.28969043,"about_ca_system_score_codex":0.000027780121,"about_ca_system_score_gemma":0.00005299612,"threshold_uncertainty_score":0.93611795},"labels":[],"label_agreement":null},{"id":"W2095204836","doi":"10.1007/s003620100065","title":"On characterizing mixtures of some life distributions","year":2001,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","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 Waterloo","funders":"","keywords":"Residual; Moment (physics); Mathematics; Exponential function; Failure rate; Statistics; Statistical physics; Applied mathematics; Mathematical analysis; Physics; Algorithm","score_opus":0.04771262246335086,"score_gpt":0.3505241582848978,"score_spread":0.30281153582154696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095204836","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":[0.021870134,0.0000135303235,0.9428728,0.0024236373,0.000111944195,0.00032341003,0.005393789,0.00015784723,0.026832908],"genre_scores_gemma":[0.9879133,0.000011881475,0.0107652545,0.0005393591,0.000045938246,0.000046926954,0.0004946661,0.000014410622,0.00016824542],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99881953,0.000053153377,0.00040307132,0.00021022586,0.0002746575,0.00023938523],"domain_scores_gemma":[0.9974637,0.0018774697,0.000109858534,0.00023611666,0.000079736914,0.00023312515],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000109734676,0.00013827268,0.00023016268,0.000041592266,0.00013947142,0.000019839285,0.000118028,0.00006327248,0.002511375],"category_scores_gemma":[0.00453125,0.0001228099,0.000057362096,0.00017941349,0.00021845876,0.00004764555,0.000021971511,0.00014203985,0.00015901464],"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":[0.000029406941,0.00020562034,0.00003482866,0.000027559536,0.000019175053,0.000004059455,0.000016135216,0.000001780197,0.0019979905,0.98755515,0.008268419,0.0018398876],"study_design_scores_gemma":[0.0005236382,0.0001079133,0.026422761,0.00004635157,0.000067393,0.000006252313,0.000041877378,0.00092275493,0.0006121912,0.96320647,0.007796034,0.0002463826],"about_ca_topic_score_codex":0.0000058419855,"about_ca_topic_score_gemma":0.0000010048238,"teacher_disagreement_score":0.9660432,"about_ca_system_score_codex":0.00004246198,"about_ca_system_score_gemma":0.00004522785,"threshold_uncertainty_score":0.99840045},"labels":[],"label_agreement":null},{"id":"W2098149189","doi":"10.1007/s00362-006-0039-y","title":"State space mixed models for longitudinal observations with binary and binomial responses","year":2007,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":43,"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":"Markov chain Monte Carlo; Multinomial distribution; State space; Count data; Mathematics; Prior probability; Markov chain; Statistical inference; Negative binomial distribution; Binary data; Covariate; Inference; Applied mathematics; Statistics; Computer science; Binary number; Monte Carlo method; Poisson distribution; Bayesian probability; Artificial intelligence","score_opus":0.12229176094158378,"score_gpt":0.3731342700055466,"score_spread":0.2508425090639628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098149189","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":[0.02692742,0.000016261152,0.96984076,0.00036292576,0.0000986574,0.00040421763,0.0011377593,0.00005430641,0.0011577025],"genre_scores_gemma":[0.15780178,0.0000070244655,0.84172535,0.00008106315,0.00005136187,0.000032092637,0.00002552172,0.000029257742,0.00024656203],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985087,0.00009362024,0.00033374023,0.00037754732,0.0002358099,0.00045059566],"domain_scores_gemma":[0.9887571,0.0105997445,0.00008179024,0.00019735363,0.000116213814,0.00024783102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007143112,0.00020606365,0.000310333,0.00007174865,0.00019574932,0.0000552852,0.00008915495,0.0000663385,0.000061556035],"category_scores_gemma":[0.0022820453,0.00015872507,0.000027025797,0.0001407453,0.00037943345,0.000093257084,0.00003714907,0.00014809742,0.0000025090135],"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":[0.0012559206,0.00007422425,0.00085515634,0.00012070288,0.000042295593,0.00005793357,0.00013739328,0.0000060907346,0.0007652672,0.9830741,0.0015365314,0.012074383],"study_design_scores_gemma":[0.0009567156,0.00070309505,0.053174242,0.00005257572,0.000104344566,0.000018336255,0.00018472281,0.0037099908,0.00013779846,0.94000137,0.00063860253,0.0003182266],"about_ca_topic_score_codex":0.000033902114,"about_ca_topic_score_gemma":0.00012911513,"teacher_disagreement_score":0.13087435,"about_ca_system_score_codex":0.000041053205,"about_ca_system_score_gemma":0.000085953034,"threshold_uncertainty_score":0.64726204},"labels":[],"label_agreement":null},{"id":"W2127555541","doi":"10.1007/s00362-007-0083-2","title":"The type I distribution of the ratio of independent “Weibullized” generalized beta-prime variables","year":2007,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","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":"Université de Moncton","funders":"National Research Foundation","keywords":"BETA (programming language); Mathematics; Generalized beta distribution; Distribution (mathematics); Prime (order theory); Beta distribution; Type (biology); Random variable; Variety (cybernetics); Combinatorics; Mathematical analysis; Statistics; Probability distribution; Computer science","score_opus":0.03454834470794218,"score_gpt":0.33779285208250204,"score_spread":0.3032445073745599,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127555541","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":[0.012634181,0.000032840835,0.9797239,0.0005383128,0.00017249535,0.0004200429,0.0014608,0.000030270314,0.004987213],"genre_scores_gemma":[0.9883716,0.000015832957,0.010957805,0.000048569753,0.000025028852,0.000015792422,0.00022780089,0.00001117364,0.00032638852],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983504,0.000119541204,0.00066419825,0.00015914872,0.00047082757,0.00023590199],"domain_scores_gemma":[0.9961332,0.0028427923,0.00026713448,0.00037458836,0.00029200563,0.000090280424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007038395,0.00012354949,0.00021676261,0.000013643072,0.00025028002,0.000018961806,0.00025259485,0.00007685703,0.00043197256],"category_scores_gemma":[0.003268739,0.0000730454,0.00006949153,0.00031380323,0.0004951687,0.000023344772,0.000058415884,0.00014518041,0.00001489686],"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":[0.00005353216,0.000086906846,0.00016429921,0.000024151,0.00003624682,3.750058e-7,0.00003319165,0.000011143678,0.0038540305,0.9906462,0.003180756,0.0019091559],"study_design_scores_gemma":[0.0016043646,0.00014466126,0.18218175,0.00006543756,0.00038209712,0.0000085506235,0.00037131074,0.0037957642,0.022766776,0.76815844,0.020141985,0.0003788459],"about_ca_topic_score_codex":0.000041730174,"about_ca_topic_score_gemma":0.000037238213,"teacher_disagreement_score":0.97573745,"about_ca_system_score_codex":0.00006652923,"about_ca_system_score_gemma":0.00009795742,"threshold_uncertainty_score":0.47297966},"labels":[],"label_agreement":null},{"id":"W2128964490","doi":"10.1007/s00362-006-0351-6","title":"Hypercubic designs and applications","year":2007,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Product Development and Customization","field":"Business, Management and Accounting","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":"University of Manitoba","funders":"","keywords":"Block (permutation group theory); Factorial experiment; Computer science; Fractional factorial design; Factorial; Arithmetic; Mathematics; Statistics; Combinatorics","score_opus":0.014875771031142808,"score_gpt":0.23112393909833112,"score_spread":0.2162481680671883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128964490","genre_codex":"other","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":[0.01544432,0.00011936636,0.4715388,0.0008900671,0.00024294389,0.0006486259,0.0000069251773,0.00029429485,0.51081467],"genre_scores_gemma":[0.9927621,0.000006388463,0.004923887,0.0013539504,0.00047669368,0.000015937938,0.00006168344,0.000012699085,0.0003866991],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994342,0.0000020977884,0.00012166744,0.00016663586,0.00010723741,0.00016816307],"domain_scores_gemma":[0.9997861,0.000059131038,0.000030320494,0.00007154449,0.00003764724,0.00001526851],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022321357,0.00007267112,0.00006800813,0.00006950754,0.0001351246,0.000068730864,0.00005315352,0.000027879329,0.00029001388],"category_scores_gemma":[0.000090518326,0.00006656348,0.0000081877915,0.00018801446,0.00006424049,0.00016947376,0.000031001488,0.000048649177,0.00023943909],"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":[0.000023609076,0.000030180772,0.008645737,0.00005593121,0.000010526801,0.000005670356,0.000021397473,0.0000025293707,0.002010989,0.81007946,0.0028236634,0.17629033],"study_design_scores_gemma":[0.0005858546,0.000008540525,0.2619933,0.000011997436,0.000074374024,0.0000043582045,0.00033023692,0.00034609722,0.00009667335,0.04956655,0.68654245,0.0004395739],"about_ca_topic_score_codex":0.000016066919,"about_ca_topic_score_gemma":0.000021242853,"teacher_disagreement_score":0.97731775,"about_ca_system_score_codex":0.000012417896,"about_ca_system_score_gemma":0.000008397678,"threshold_uncertainty_score":0.31754485},"labels":[],"label_agreement":null},{"id":"W2592561635","doi":"10.1007/s00362-017-0887-7","title":"Using SeDuMi to find various optimal designs for regression models","year":2017,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","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":"University of Victoria","funders":"National Institute of General Medical Sciences","keywords":"Mathematical optimization; Optimal design; Semidefinite programming; Mathematics; Estimator; Discretization; Computer science; Focus (optics); Linear programming; Nonlinear programming; Equivalence (formal languages); Nonlinear system; Machine learning","score_opus":0.4964396165725281,"score_gpt":0.5570098859689532,"score_spread":0.06057026939642507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2592561635","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":[0.01037971,0.000025236615,0.9729118,0.00027268258,0.0004931853,0.0005869574,0.00025654232,0.000029973418,0.015043931],"genre_scores_gemma":[0.34394953,8.376957e-7,0.65442115,0.00023426951,0.000061570034,0.000027096936,0.0000040069535,0.00002330102,0.0012782764],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99679494,0.0002819761,0.00053709524,0.0008003489,0.0010473859,0.0005382461],"domain_scores_gemma":[0.995019,0.0030789073,0.00021783393,0.0009971384,0.00020962511,0.00047749773],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0023104486,0.00024327108,0.00042807785,0.000119825134,0.0009815631,0.00076515146,0.0010955109,0.00012471748,0.00063556345],"category_scores_gemma":[0.009216588,0.00017813411,0.00010238266,0.00011472868,0.00030417874,0.00041446908,0.00030723718,0.00014153625,0.00014317827],"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":[0.0017086272,0.00023548504,0.0002327643,0.000021541067,0.00006208587,0.000117257674,0.0017032588,0.04910829,0.5227506,0.18483178,0.016179688,0.22304863],"study_design_scores_gemma":[0.0016133904,0.0010308732,0.003343775,0.000081583144,0.00006889814,0.000026936066,0.0009970346,0.7808322,0.01129725,0.1942298,0.0055712406,0.0009070693],"about_ca_topic_score_codex":0.00009409669,"about_ca_topic_score_gemma":0.0000055935084,"teacher_disagreement_score":0.73172385,"about_ca_system_score_codex":0.000108761764,"about_ca_system_score_gemma":0.00014388344,"threshold_uncertainty_score":0.9991292},"labels":[],"label_agreement":null},{"id":"W2623410672","doi":"10.1007/s00362-017-0920-x","title":"Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton (2017): modern data science with R, Chapman and Hall/CRC, 556 pp., $$\\pounds $$ £ 51.19, ISBN 978-1498724487","year":2017,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Data Analysis with R","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":"Art history; Philosophy; Art","score_opus":0.03567625716390627,"score_gpt":0.3045890809143503,"score_spread":0.268912823750444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2623410672","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":[0.002871262,0.0007103124,0.92599946,0.0031367512,0.0004608466,0.00051552546,0.0013270921,0.00026545784,0.06471328],"genre_scores_gemma":[0.7544412,0.00047916215,0.24138898,0.0009122581,0.00013666715,0.00001788879,0.00042022296,0.000054572607,0.0021490566],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9946599,0.00009661393,0.0004629468,0.0022581369,0.0014803498,0.0010420405],"domain_scores_gemma":[0.9925217,0.00034339863,0.00032625961,0.0057492247,0.00017816568,0.0008812302],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0013864978,0.00045435238,0.00053417904,0.00018177654,0.0017715234,0.0025885717,0.0073857745,0.00011005637,0.00006400194],"category_scores_gemma":[0.0010706095,0.00036773263,0.000037542603,0.00037489797,0.0025318586,0.0041484646,0.0034579493,0.00045584998,0.000096549484],"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":[0.00018693495,0.00050092203,0.0085896095,0.00016741526,0.0004009121,0.0012675755,0.001215582,0.00007614123,0.0057673804,0.5393024,0.05572173,0.3868034],"study_design_scores_gemma":[0.0032168648,0.0010593146,0.1211839,0.000204441,0.00047033446,0.00043380394,0.00021793,0.6716252,0.00022344755,0.013990079,0.18476145,0.0026132655],"about_ca_topic_score_codex":0.0012014712,"about_ca_topic_score_gemma":0.0009973667,"teacher_disagreement_score":0.7515699,"about_ca_system_score_codex":0.00009971864,"about_ca_system_score_gemma":0.0005261823,"threshold_uncertainty_score":0.99987745},"labels":[],"label_agreement":null},{"id":"W2770810030","doi":"10.1007/s00362-017-0966-9","title":"On the consistency of the P–C estimator in a nonparametric regression model","year":2017,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Probability and Risk Models","field":"Decision Sciences","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":"McMaster University","funders":"","keywords":"Consistency (knowledge bases); Estimator; Nonparametric regression; Strong consistency; Nonparametric statistics; Statistics; Mathematics; Regression function; Regression; Regression analysis; Convergence (economics); Function (biology); Econometrics; Applied mathematics; Discrete mathematics; Economics","score_opus":0.14731337918143647,"score_gpt":0.4141911795848233,"score_spread":0.2668778004033868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2770810030","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":[0.7008741,0.00010334574,0.056122597,0.020165516,0.0007185053,0.0011169062,0.0004036974,0.000024380633,0.22047094],"genre_scores_gemma":[0.9953289,0.0000049054365,0.0039931643,0.00023942646,0.000004861782,0.000009107426,2.72816e-7,0.000004010037,0.00041535444],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978954,0.00024131626,0.00042086936,0.00030118407,0.0009594679,0.00018171844],"domain_scores_gemma":[0.99216366,0.0060968013,0.00023335074,0.0013554684,0.00008700454,0.00006370539],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0018882366,0.00009653901,0.00022293977,0.000060190785,0.0004985657,0.000106125524,0.0012504144,0.00006396012,0.00017468282],"category_scores_gemma":[0.047257345,0.00003600445,0.00007933433,0.0002163422,0.0010669967,0.00007644436,0.00021407616,0.00023377324,0.000050005925],"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":[0.00007140119,0.00009178419,0.0037345607,0.000005277666,0.0000039588344,0.0000034574532,0.00019207424,0.0041895583,0.0001598774,0.9709382,0.0022902351,0.01831959],"study_design_scores_gemma":[0.00016806056,0.000029071496,0.047442604,0.000040501927,0.0000049601053,8.8578645e-7,0.0000697122,0.21176603,0.000045069748,0.7403183,0.00006044371,0.00005435104],"about_ca_topic_score_codex":0.000073806965,"about_ca_topic_score_gemma":0.00011081956,"teacher_disagreement_score":0.29445478,"about_ca_system_score_codex":0.000027452772,"about_ca_system_score_gemma":0.00013869225,"threshold_uncertainty_score":0.960768},"labels":[],"label_agreement":null},{"id":"W2798711685","doi":"10.1007/s00362-022-01333-9","title":"On the circular correlation coefficients for bivariate von Mises distributions on a torus","year":2022,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","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 Waterloo","funders":"","keywords":"von Mises distribution; Mathematics; Bivariate analysis; Estimator; Univariate; Statistics; von Mises yield criterion; Applied mathematics; Parametric statistics; Multivariate statistics","score_opus":0.01994508815286599,"score_gpt":0.27623437866285805,"score_spread":0.25628929050999205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2798711685","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":[0.00029083656,0.000009338667,0.9927633,0.0019994406,0.0005157494,0.00035671255,0.0005343315,0.00004739017,0.0034829048],"genre_scores_gemma":[0.9158422,0.000001026481,0.08213928,0.0015136542,0.000028194472,0.00016328153,0.00007928542,0.000009397312,0.00022369665],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987798,0.00024047811,0.00013920563,0.00030663575,0.00030525928,0.00022867284],"domain_scores_gemma":[0.99799234,0.0015478617,0.00004573882,0.000311119,0.000029500334,0.00007346156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042274335,0.00009976446,0.00009960499,0.00003071317,0.0006637847,0.00006424825,0.0003411397,0.000024861121,0.00011118834],"category_scores_gemma":[0.00051228126,0.0000723275,0.00005610678,0.00019716464,0.000050211045,0.000028698618,0.00008054915,0.00017535714,0.000015010049],"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":[0.000024039422,0.00007893994,0.0000037251598,0.000003202797,0.000009367065,0.000004064898,0.00009503511,0.00085844,0.00017549103,0.9748932,0.003431715,0.020422745],"study_design_scores_gemma":[0.0007037208,0.00086692604,0.001427772,0.000014477659,0.00003585867,0.000006653733,0.00004865938,0.37514442,0.000087236265,0.586491,0.03487666,0.0002966317],"about_ca_topic_score_codex":0.000007930382,"about_ca_topic_score_gemma":5.1664244e-7,"teacher_disagreement_score":0.91555136,"about_ca_system_score_codex":0.00009590603,"about_ca_system_score_gemma":0.000048944057,"threshold_uncertainty_score":0.51053625},"labels":[],"label_agreement":null},{"id":"W2799840411","doi":"10.1007/s00362-018-1000-6","title":"Random coefficient minification processes","year":2018,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":4,"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, Okanagan Campus; Kelowna General Hospital; University of British Columbia","funders":"University of British Columbia","keywords":"Minification; Series (stratigraphy); Transformation (genetics); Flexibility (engineering); Time series; Computer science; Applied mathematics; Autoregressive–moving-average model; Mathematics; Algorithm; Mathematical optimization; Econometrics; Statistics; Autoregressive model; Geology","score_opus":0.007440012996304371,"score_gpt":0.2480900614433359,"score_spread":0.24065004844703153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2799840411","genre_codex":"other","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":[0.1701046,0.00003122628,0.16563968,0.0011975577,0.0001936879,0.00026344787,0.000044339857,0.00010836166,0.6624171],"genre_scores_gemma":[0.9955553,0.000004510025,0.0029012782,0.0004268906,0.00003896794,0.000009377922,0.000017543482,0.0000042817655,0.0010418822],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993055,0.000039540428,0.00011656866,0.0002129439,0.00015780448,0.0001676772],"domain_scores_gemma":[0.9996035,0.00016682828,0.000026083278,0.00011562682,0.0000098714645,0.000078072946],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00013311948,0.00006479887,0.000085309395,0.000011785733,0.00014287588,0.000010629503,0.00009233473,0.00003808529,0.017351978],"category_scores_gemma":[0.000348354,0.000051298866,0.000016034877,0.00020569294,0.00064530544,0.000035217625,0.000028396997,0.000043998913,0.0036270553],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00312945,0.0026342524,0.27050525,0.00021592522,0.00048063608,0.00018822309,0.01325025,0.0072577833,0.07145226,0.052807152,0.35118285,0.22689597],"study_design_scores_gemma":[0.0052744425,0.0013943479,0.30251062,0.00002780948,0.0005725057,0.000042701162,0.00072618097,0.050327606,0.008872519,0.018523842,0.61017936,0.0015480422],"about_ca_topic_score_codex":0.000044381435,"about_ca_topic_score_gemma":0.00019171741,"teacher_disagreement_score":0.82545066,"about_ca_system_score_codex":0.000025558324,"about_ca_system_score_gemma":0.000009923831,"threshold_uncertainty_score":0.99714875},"labels":[],"label_agreement":null},{"id":"W2908726971","doi":"10.1007/s00362-021-01265-w","title":"Confidence intervals with higher accuracy for short and long-memory linear processes","year":2021,"lang":"en","type":"preprint","venue":"Statistical Papers","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":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Statistics Canada; Canadian Blood Services; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Confidence interval; Mathematics; Limit (mathematics); Applied mathematics; Sample size determination; Central limit theorem; Population; Statistics; Long memory; Econometrics; Mathematical analysis; Demography","score_opus":0.03621878776434152,"score_gpt":0.33287002122305637,"score_spread":0.29665123345871486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2908726971","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":[0.0003372063,0.0009940179,0.9952964,0.00076412235,0.00037813355,0.0005743948,0.00010577878,0.00009270492,0.001457229],"genre_scores_gemma":[0.12213109,0.00014485363,0.87576103,0.0010724703,0.00012755918,0.00016111037,0.00005169007,0.000028878114,0.0005213145],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978336,0.00012641569,0.0003275334,0.0010481125,0.00030042251,0.0003639229],"domain_scores_gemma":[0.99720925,0.0015353626,0.00009865334,0.0005942638,0.0003258844,0.00023655647],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034538744,0.00034065824,0.0005189836,0.000046203153,0.00009064311,0.0004033171,0.0006271866,0.00019865931,0.00008125798],"category_scores_gemma":[0.00072951557,0.00026404776,0.000055770848,0.00012023595,0.0002320966,0.00017977312,0.00066315354,0.00044993148,0.0000016757392],"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":[0.00018383597,0.00021309957,0.00017254752,0.007269346,0.0004213989,0.00061538175,0.0019637668,0.00011079531,0.0004756124,0.50195247,0.0017035973,0.48491818],"study_design_scores_gemma":[0.0047554,0.0033761368,0.02213437,0.010564726,0.0016083246,0.0006129162,0.00046658047,0.10059915,0.0075318525,0.81615424,0.02267758,0.009518721],"about_ca_topic_score_codex":0.000018699902,"about_ca_topic_score_gemma":0.000037255035,"teacher_disagreement_score":0.47539943,"about_ca_system_score_codex":0.000029938727,"about_ca_system_score_gemma":0.0005103698,"threshold_uncertainty_score":0.99998116},"labels":[],"label_agreement":null},{"id":"W2908858115","doi":"10.1007/s00362-018-01076-6","title":"Properties of optimal regression designs under the second-order least squares estimator","year":2019,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":4,"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 Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Applied mathematics; Polynomial regression; Equivalence (formal languages); Estimator; Optimal design; Generalized least squares; Nonlinear regression; Non-linear least squares; Mathematical optimization; Least-squares function approximation; Linear regression; Regression analysis; Statistics; Discrete mathematics","score_opus":0.14110002371706523,"score_gpt":0.41578880930191625,"score_spread":0.274688785584851,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2908858115","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":[0.64753336,0.0009772574,0.27260393,0.0014880309,0.00125005,0.0015985332,0.00022755896,0.00011891277,0.07420238],"genre_scores_gemma":[0.85007674,0.0000020639495,0.14420916,0.00026877812,0.0000239337,0.000019286985,0.00000254512,0.000023920122,0.0053735822],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9961487,0.0008130399,0.00067614915,0.00055057585,0.0014353483,0.00037617807],"domain_scores_gemma":[0.9958734,0.0028435045,0.00020530229,0.00068001554,0.00023619311,0.00016160132],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0018191902,0.00023912043,0.00043520296,0.00009448561,0.00017455718,0.00015837011,0.0007496838,0.00009937084,0.011720067],"category_scores_gemma":[0.0020351193,0.00011782664,0.00009907894,0.00043241086,0.00074028753,0.00021789584,0.00019780426,0.0002345568,0.0007738888],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007832453,0.00019760313,0.0014728548,0.00006379253,0.00006910028,0.000012854375,0.0012729568,0.0031071396,0.8539827,0.11559288,0.0064470978,0.016997805],"study_design_scores_gemma":[0.0064081238,0.005061688,0.07211877,0.00085661863,0.00021852968,0.00016639961,0.10644298,0.1341312,0.56195325,0.073081054,0.036178388,0.0033829752],"about_ca_topic_score_codex":0.000026799427,"about_ca_topic_score_gemma":0.0000073358747,"teacher_disagreement_score":0.29202938,"about_ca_system_score_codex":0.000045774883,"about_ca_system_score_gemma":0.00016657676,"threshold_uncertainty_score":0.9947033},"labels":[],"label_agreement":null},{"id":"W2916966508","doi":"10.1007/s00362-019-01096-w","title":"David A. Harville: Linear models and the relevant distributions and matrix algebra","year":2019,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Soil Geostatistics and Mapping","field":"Environmental 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":"Linear algebra; Algebra over a field; Mathematics; Matrix (chemical analysis); Pure mathematics; Chemistry; Geometry","score_opus":0.007440044956761377,"score_gpt":0.23772030560850896,"score_spread":0.2302802606517476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916966508","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":[0.45271552,0.0008440208,0.3207297,0.009928922,0.00068868865,0.0024769346,0.0035639117,0.00019689095,0.2088554],"genre_scores_gemma":[0.9894745,0.00015742055,0.009226044,0.00025252832,0.000013691808,0.000011697951,0.000043672906,0.000009125961,0.00081131683],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991882,0.00004421907,0.00014032776,0.0002419345,0.00017487262,0.00021045942],"domain_scores_gemma":[0.99919903,0.0005025783,0.00002919364,0.00014930034,0.0000051792654,0.000114694296],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00018486721,0.00009882588,0.00012905081,0.0000071366153,0.0001520743,0.000040453873,0.00007404353,0.00003360089,0.00092972064],"category_scores_gemma":[0.00016049703,0.00006521675,0.000014758954,0.00006241561,0.0005436835,0.000060701343,0.00016114957,0.00011678898,0.00018662943],"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":[0.000050781528,0.000021496964,0.0034376923,0.000021379274,0.000018543342,0.000008697327,0.00030588955,0.00032091417,0.00037310526,0.9844314,0.0023762165,0.008633885],"study_design_scores_gemma":[0.0039624707,0.0001909839,0.21021831,0.000044745946,0.0001582581,0.000055409455,0.00078059745,0.3508981,0.000020792775,0.35872495,0.074249096,0.0006962895],"about_ca_topic_score_codex":0.00031555182,"about_ca_topic_score_gemma":0.000037376674,"teacher_disagreement_score":0.62570643,"about_ca_system_score_codex":0.00002475264,"about_ca_system_score_gemma":0.000006829549,"threshold_uncertainty_score":0.99998355},"labels":[],"label_agreement":null},{"id":"W2967342937","doi":"10.1007/s00362-023-01515-z","title":"Inference for continuous-time long memory randomly sampled processes","year":2023,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Stochastic processes and financial applications","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":"Carleton University","funders":"","keywords":"Gaussian process; Inference; Focus (optics); Gaussian; Process (computing); Computer science; Discrete time and continuous time; Discrete-time stochastic process; Algorithm; Mathematics; Applied mathematics; Stochastic process; Statistics; Continuous-time stochastic process; Artificial intelligence","score_opus":0.027278940600274772,"score_gpt":0.26498847035873757,"score_spread":0.2377095297584628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967342937","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":[0.0012434238,0.00022527717,0.97978574,0.00069304864,0.00014290419,0.0006401377,0.0022828975,0.00017550359,0.014811074],"genre_scores_gemma":[0.97868353,0.000115017756,0.014003783,0.00057682936,0.00027969969,0.0013594175,0.000666032,0.000069824586,0.004245838],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987183,0.0000027461128,0.00044750926,0.00040847022,0.000046102938,0.00037686373],"domain_scores_gemma":[0.9981383,0.0013498057,0.00014133529,0.00017674344,0.00008627823,0.00010750973],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00027054155,0.00014316637,0.0003966272,0.00009858542,0.00018338513,0.0000603907,0.00019415116,0.000074641874,0.0003934545],"category_scores_gemma":[0.0039384873,0.00015442609,0.00005711831,0.00043294163,0.00012019613,0.00007216526,0.00003911988,0.00008082646,0.0016716494],"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":[0.00008229734,0.00004404909,0.00048248156,0.00018599912,0.000030050476,0.0000027576527,0.00015954385,0.0000257885,0.00005451076,0.9910553,0.0022014242,0.00567576],"study_design_scores_gemma":[0.0023735256,0.00016419563,0.017195323,0.000031779156,0.000026332951,0.0000020204488,0.000093736264,0.0035117937,0.000035783643,0.94036925,0.035692543,0.00050370814],"about_ca_topic_score_codex":0.00006257612,"about_ca_topic_score_gemma":0.000025850846,"teacher_disagreement_score":0.9774401,"about_ca_system_score_codex":0.000029300396,"about_ca_system_score_gemma":0.00007162372,"threshold_uncertainty_score":0.9991057},"labels":[],"label_agreement":null},{"id":"W316531273","doi":"10.1007/s00362-015-0688-9","title":"D-optimal designs based on the second-order least squares estimator","year":2015,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","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 Victoria","funders":"","keywords":"Mathematics; Optimal design; Estimator; Applied mathematics; Mathematical optimization; Least-squares function approximation; Univariate; Polynomial; Polynomial regression; Regression analysis; Statistics; Multivariate statistics","score_opus":0.23009796809667618,"score_gpt":0.4446194924701144,"score_spread":0.21452152437343822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W316531273","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":[0.0077147866,0.000050889077,0.7530712,0.002828727,0.00066100346,0.000565324,0.00030876408,0.00012169533,0.2346776],"genre_scores_gemma":[0.5569759,1.8028216e-7,0.43784198,0.0023896703,0.00006221699,0.00004719405,0.00000767445,0.00003107695,0.0026441081],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99486625,0.0013292847,0.00055783003,0.0006731974,0.0020715622,0.0005018742],"domain_scores_gemma":[0.9869541,0.011362747,0.00012301138,0.0007527008,0.00026939358,0.00053802854],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00397359,0.00028473954,0.00035293668,0.00012323447,0.00025376567,0.00037747782,0.0008363651,0.000099230856,0.015492361],"category_scores_gemma":[0.017698238,0.00016409517,0.000094136216,0.0006028974,0.00064572814,0.00014250845,0.000102008955,0.000309018,0.002592872],"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":[0.0023075475,0.000837023,0.0020585016,0.000020512105,0.0000867247,0.0003369657,0.0015994291,0.036614764,0.019465094,0.47914034,0.4053476,0.052185494],"study_design_scores_gemma":[0.0038417743,0.004182808,0.009737058,0.00006301948,0.000073052666,0.000041945197,0.012533122,0.72787035,0.009974626,0.07403611,0.15585843,0.0017877053],"about_ca_topic_score_codex":0.000018959501,"about_ca_topic_score_gemma":0.000010141977,"teacher_disagreement_score":0.69125557,"about_ca_system_score_codex":0.000107676045,"about_ca_system_score_gemma":0.00033447533,"threshold_uncertainty_score":0.9981837},"labels":[],"label_agreement":null},{"id":"W3194623631","doi":"10.1007/s00362-021-01252-1","title":"Approximate likelihood with proxy variables for parameter estimation in high-dimensional factor copula models","year":2021,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":8,"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","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Copula (linguistics); Econometrics; Mathematics; Proxy (statistics); Latent variable; Statistics","score_opus":0.027758386786389522,"score_gpt":0.23853310913624715,"score_spread":0.2107747223498576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194623631","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":[0.119501084,0.00014210817,0.8774689,0.00017823624,0.00011302675,0.00034437052,0.0014095661,0.000024619347,0.0008180773],"genre_scores_gemma":[0.7191919,0.000009287661,0.28032458,0.000106070904,0.000014792104,0.00006736453,0.00021065785,0.000018222701,0.000057137157],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986672,0.000015758593,0.0004654807,0.00046057106,0.0000581496,0.0003328821],"domain_scores_gemma":[0.99930614,0.0002918453,0.00009756119,0.000170328,0.00005412986,0.00007998036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020481941,0.00014728463,0.00036147155,0.00006730786,0.000076726836,0.00005300966,0.00006345779,0.00009535505,0.00014813649],"category_scores_gemma":[0.00043893987,0.0001477939,0.000039622922,0.00013926017,0.0000479963,0.0001634542,0.000024409208,0.00012767366,0.000017344813],"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":[0.00016167048,0.0001790148,0.0055771377,0.00012643717,0.00003190456,0.000011310675,0.00021749428,0.032972626,0.000045222412,0.9551298,0.00007151131,0.0054758526],"study_design_scores_gemma":[0.00058730313,0.000060008726,0.0041141347,0.000023409562,0.000005327127,0.0000010804794,0.000011568882,0.6053916,0.000028838796,0.38954046,0.00008707032,0.00014915683],"about_ca_topic_score_codex":0.00022453752,"about_ca_topic_score_gemma":0.00009268308,"teacher_disagreement_score":0.5996908,"about_ca_system_score_codex":0.00008106641,"about_ca_system_score_gemma":0.00007622198,"threshold_uncertainty_score":0.602686},"labels":[],"label_agreement":null},{"id":"W3202032933","doi":"10.1007/s00362-021-01266-9","title":"Asymptotic analysis of reliability measures for an imperfect dichotomous test","year":2021,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","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 Waterloo","funders":"","keywords":"Reliability (semiconductor); Statistics; Consistency (knowledge bases); Mathematics; Convergence (economics); Test (biology); Econometrics; Imperfect; Gold standard (test); Aggregate (composite); Economics","score_opus":0.054536120320851075,"score_gpt":0.3835623732133685,"score_spread":0.3290262528925174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3202032933","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":[0.010954213,0.000009428995,0.975883,0.0001914718,0.00003287846,0.00033056224,0.007771877,0.00007591542,0.0047506234],"genre_scores_gemma":[0.909029,0.0000033105214,0.08963887,0.00008706949,0.000014687926,0.00010222377,0.0009838825,0.000014011903,0.00012695183],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984999,0.00010835513,0.0005025693,0.0003589057,0.00030515922,0.0002251166],"domain_scores_gemma":[0.99201703,0.006776154,0.00010362974,0.0004320804,0.00046688394,0.00020424278],"candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00034901925,0.00013636972,0.000416669,0.00006195709,0.00011723226,0.000028202934,0.000111299036,0.00007120766,0.0011137002],"category_scores_gemma":[0.019247102,0.00012532703,0.00015010197,0.0006379134,0.00021028178,0.000039881626,0.000019862387,0.00008747516,0.000009696211],"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":[0.000022034645,0.00062739453,0.00096750417,0.00010447501,0.0002278617,0.0000019711988,0.00006502263,0.00009119457,0.0040076403,0.9880314,0.0012443013,0.004609213],"study_design_scores_gemma":[0.0014341447,0.000522351,0.22003005,0.000033329947,0.006159474,0.0000067280353,0.00047385498,0.11760681,0.0033060086,0.64694524,0.002803276,0.0006787199],"about_ca_topic_score_codex":0.000016880289,"about_ca_topic_score_gemma":0.00009020361,"teacher_disagreement_score":0.8980748,"about_ca_system_score_codex":0.000060786762,"about_ca_system_score_gemma":0.00010763872,"threshold_uncertainty_score":0.99979943},"labels":[],"label_agreement":null},{"id":"W4225429113","doi":"10.1007/s00362-022-01317-9","title":"Constructing K-optimal designs for regression models","year":2022,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","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":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Multicollinearity; Polynomial regression; Design matrix; Applied mathematics; Optimal design; Estimator; Regression analysis; Mathematical optimization; Convexity; Regression; Linear regression; Statistics","score_opus":0.25308950876934433,"score_gpt":0.47460593235966464,"score_spread":0.2215164235903203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225429113","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":[0.0032585121,0.00006717723,0.9527953,0.00024996453,0.00056850706,0.00045263706,0.0005808469,0.00006169352,0.041965336],"genre_scores_gemma":[0.3952518,5.9397115e-7,0.6032907,0.00022662546,0.00003267707,0.00012212737,0.00002024745,0.000019134015,0.0010360708],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961166,0.0008102812,0.0005826597,0.00065976096,0.0014048341,0.00042590188],"domain_scores_gemma":[0.99144894,0.007710246,0.0001686793,0.00035765395,0.00010291437,0.00021156258],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003290407,0.00017539156,0.00033400502,0.00013043189,0.0006705102,0.0001371409,0.0005775985,0.000043684075,0.004629318],"category_scores_gemma":[0.0037748616,0.0001383413,0.00011597158,0.000376127,0.00027192073,0.00017763935,0.00031003388,0.00023369693,0.000034059187],"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":[0.00062632037,0.0000933035,0.00018201108,0.0000065533345,0.000023428207,0.000038488484,0.00068426604,0.011767072,0.024471374,0.7272093,0.014070379,0.22082746],"study_design_scores_gemma":[0.0016742607,0.0012416269,0.00011378147,0.000011623659,0.000039952596,0.00009363715,0.03021297,0.48611704,0.003831389,0.46027094,0.015719477,0.0006732894],"about_ca_topic_score_codex":0.000012367558,"about_ca_topic_score_gemma":0.0000012905334,"teacher_disagreement_score":0.47434998,"about_ca_system_score_codex":0.00018684306,"about_ca_system_score_gemma":0.0001192719,"threshold_uncertainty_score":0.9962806},"labels":[],"label_agreement":null},{"id":"W4286741934","doi":"10.1007/s00362-022-01339-3","title":"Correction to: On efficiency of some restricted estimators in a multivariate regression model","year":2022,"lang":"en","type":"article","venue":"Statistical Papers","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 Windsor","funders":"","keywords":"Multivariate statistics; Estimator; Econometrics; Statistics; Regression analysis; Bayesian multivariate linear regression; Regression; Computer science; Mathematics","score_opus":0.07311681432887482,"score_gpt":0.4215879521226827,"score_spread":0.3484711377938079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286741934","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":[0.022723408,0.000005314849,0.9731146,0.0000856005,0.00042789953,0.0003958266,0.00032124974,0.000051910785,0.0028741818],"genre_scores_gemma":[0.56256425,0.0000011228066,0.43697253,0.00009167222,0.000007990505,0.000067724046,0.000009632855,0.000021080215,0.00026398033],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981757,0.00026293864,0.00044380853,0.00036031767,0.00045692557,0.0003003223],"domain_scores_gemma":[0.9960049,0.0034821369,0.00010917588,0.00022466399,0.000034605804,0.00014455432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003292424,0.00016032491,0.00032957172,0.00016479779,0.00013083154,0.00000570763,0.00013387385,0.000036686622,0.00012334369],"category_scores_gemma":[0.007132276,0.00013783746,0.0000374242,0.00034881372,0.00006385736,0.000034915873,0.00010538166,0.00037094226,0.000003590224],"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":[0.00057203136,0.00053327286,0.00002062107,0.000049357044,0.000007553711,0.000036403624,0.0005933,0.1471171,0.0059204125,0.823714,0.0017127392,0.019723205],"study_design_scores_gemma":[0.00051983376,0.00045326367,0.00045122774,0.000068943125,0.000013626226,0.0000015135257,0.00013306974,0.6048801,0.00018717619,0.39309055,0.000042634005,0.00015808443],"about_ca_topic_score_codex":0.000052151827,"about_ca_topic_score_gemma":0.0000067998894,"teacher_disagreement_score":0.5398409,"about_ca_system_score_codex":0.0001714222,"about_ca_system_score_gemma":0.00006899417,"threshold_uncertainty_score":0.8538516},"labels":[],"label_agreement":null},{"id":"W4309120467","doi":"10.1007/s00362-022-01374-0","title":"Bounds for Gini’s mean difference based on first four moments, with some applications","year":2022,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":8,"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":"National Natural Science Foundation of China","keywords":"Kurtosis; Mathematics; Skewness; Statistics; Variance (accounting); Inequality; Independent and identically distributed random variables; Random variable; Dispersion (optics); Index (typography); Gini coefficient; Econometrics; Economic inequality; Computer science; Mathematical analysis; Economics","score_opus":0.053233882211199735,"score_gpt":0.3263739790183574,"score_spread":0.2731400968071577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309120467","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":[0.00020663814,0.000002820249,0.9826562,0.0022560027,0.00003695712,0.0011666663,0.008469981,0.00014467472,0.005060059],"genre_scores_gemma":[0.90936667,0.0000010837128,0.08071677,0.0011322259,0.0000443981,0.0067697237,0.0010777145,0.00004174467,0.0008496651],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99842876,0.000053879503,0.00030345315,0.00039893374,0.0004949527,0.00032004362],"domain_scores_gemma":[0.996551,0.0026921644,0.000105193154,0.00037191686,0.00007753484,0.00020224154],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00015675552,0.00018839787,0.00021515103,0.000059462476,0.001037842,0.00004998705,0.00022349773,0.000032154825,0.0016681524],"category_scores_gemma":[0.00037079994,0.00016773773,0.000050571023,0.00022892735,0.00018039577,0.000026427459,0.000037600188,0.00018879292,0.00003992337],"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":[0.00008476779,0.0003753915,0.00002479981,0.0000695421,0.000019782097,0.000001851701,0.00004176184,0.00035239558,0.000030891508,0.9922491,0.005067495,0.0016822481],"study_design_scores_gemma":[0.0030390911,0.00096382655,0.010516011,0.000031087162,0.00020967305,0.0000073718206,0.0003385473,0.11575319,0.0000265952,0.7444021,0.12398065,0.0007318726],"about_ca_topic_score_codex":0.000007466831,"about_ca_topic_score_gemma":0.000016747701,"teacher_disagreement_score":0.90916,"about_ca_system_score_codex":0.00020773913,"about_ca_system_score_gemma":0.00008518181,"threshold_uncertainty_score":0.99924445},"labels":[],"label_agreement":null},{"id":"W4312201186","doi":"10.1007/s00362-022-01388-8","title":"On the distribution of sample scale-free scatter matrices","year":2022,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Random Matrices and Applications","field":"Mathematics","cited_by":1,"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; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Matrix (chemical analysis); Multivariate normal distribution; Scatter matrix; Positive-definite matrix; Hypergeometric function; Wishart distribution; Random matrix; Scale (ratio); Applied mathematics; Diagonal; Function (biology); Square matrix; Statistics; Mathematical analysis; Multivariate statistics; Symmetric matrix","score_opus":0.020901706425918497,"score_gpt":0.28764690825824996,"score_spread":0.26674520183233147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312201186","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":[0.6345014,0.00012548275,0.24136627,0.02363411,0.00039344392,0.002482308,0.033311106,0.00024819624,0.063937716],"genre_scores_gemma":[0.9948504,0.0000049380874,0.004459864,0.00022009465,0.000025637546,0.00014484096,0.00012183025,0.000011381723,0.00016100955],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99911237,0.00008572776,0.00020906003,0.00013492502,0.0003188012,0.0001390889],"domain_scores_gemma":[0.9952289,0.0042762244,0.000086745466,0.00034877082,0.000021876165,0.00003750898],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00026343146,0.00007503341,0.00012587238,0.000016753464,0.00027536094,0.0000144630885,0.0002733848,0.000015336585,0.0025183896],"category_scores_gemma":[0.000674871,0.000050228482,0.000050733808,0.0001835931,0.000094962066,0.000013085932,0.000103148384,0.00013349799,0.000016845352],"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":[0.000038643146,0.000096267955,0.00011211687,0.000023605528,0.000012580711,5.05052e-7,0.00006709622,0.000022172744,0.00006228523,0.9201039,0.07858377,0.0008770702],"study_design_scores_gemma":[0.0005414173,0.000104112216,0.002104796,0.000006209413,0.00006636485,0.0000025519714,0.0004421646,0.0004450796,0.00006362345,0.9753976,0.020713774,0.00011230572],"about_ca_topic_score_codex":0.000061892766,"about_ca_topic_score_gemma":0.000008388888,"teacher_disagreement_score":0.36034903,"about_ca_system_score_codex":0.00003758246,"about_ca_system_score_gemma":0.000015703596,"threshold_uncertainty_score":0.9983934},"labels":[],"label_agreement":null},{"id":"W4317830835","doi":"10.1007/s00362-023-01394-4","title":"On some problems of Bayesian region construction with guaranteed coverages","year":2023,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"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","keywords":"Bayesian probability; Algorithm; Computer science; Statistics; A priori and a posteriori; Mathematics; Artificial intelligence","score_opus":0.0569271963954886,"score_gpt":0.3579628342160311,"score_spread":0.3010356378205425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317830835","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":[0.005217179,0.000005262626,0.9869809,0.00016243085,0.00009256009,0.00031902007,0.00020886693,0.00013579903,0.0068779467],"genre_scores_gemma":[0.5172743,0.00002671308,0.4821679,0.0001143192,0.000025247933,0.000033477696,0.000024035107,0.000041132724,0.00029285322],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99871385,0.00010591686,0.00030443032,0.00028318132,0.00031397634,0.0002786161],"domain_scores_gemma":[0.99681723,0.002712348,0.000111075766,0.00020712902,0.000050784904,0.00010140188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018087463,0.00016005353,0.00032310007,0.0000760468,0.00007401742,0.000010706067,0.000072468996,0.00006425213,0.00007636878],"category_scores_gemma":[0.0012368214,0.00011773424,0.000033794513,0.00019678973,0.00032528563,0.000049638606,0.000018151257,0.0001567061,0.000012984657],"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":[0.00017027096,0.0000448423,0.000030862302,0.00022122079,0.000030841187,0.000045295994,0.00011606801,0.0002755313,0.0006884704,0.98266023,0.00063287414,0.015083512],"study_design_scores_gemma":[0.00061015034,0.0005077939,0.00023158439,0.00016284254,0.00004082123,0.000015407015,0.00015414508,0.0022259275,0.00021403344,0.9954877,0.0001857204,0.00016387009],"about_ca_topic_score_codex":0.0000078149815,"about_ca_topic_score_gemma":0.000005150134,"teacher_disagreement_score":0.5120571,"about_ca_system_score_codex":0.000027286143,"about_ca_system_score_gemma":0.000030414332,"threshold_uncertainty_score":0.4801063},"labels":[],"label_agreement":null},{"id":"W4386421016","doi":"10.1007/s00362-023-01469-2","title":"Bayesian and maximin A-optimal designs for spline regression models with unknown knots","year":2023,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":0,"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 Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Minimax; Optimal design; Mathematical optimization; Mathematics; Bayesian probability; Optimality criterion; Prior probability; Quadratic equation; Algorithm; Statistics","score_opus":0.18987846769652303,"score_gpt":0.4530553777483672,"score_spread":0.2631769100518442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386421016","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":[0.0059092194,0.000059911843,0.9852228,0.00048659396,0.00012851029,0.00054517295,0.00019227412,0.00011541818,0.0073400787],"genre_scores_gemma":[0.28995407,0.0000126052,0.70728993,0.00013762609,0.000040557086,0.00007183778,0.000030048246,0.000035855683,0.0024274655],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969799,0.00028631842,0.0004716936,0.0007938388,0.0009586279,0.0005096474],"domain_scores_gemma":[0.99402386,0.0050053173,0.00010456467,0.00037026822,0.00013004607,0.00036591582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019264343,0.00025272457,0.0004033843,0.00019511626,0.0002496633,0.00019155382,0.00031293338,0.000103388644,0.00036804785],"category_scores_gemma":[0.0018630035,0.00015865477,0.00005559608,0.0006223091,0.0003998437,0.00023169431,0.00012694135,0.00013824586,0.000079618454],"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":[0.003400972,0.00020250282,0.00034650776,0.00007058114,0.00008742167,0.00029370104,0.0016189436,0.012056429,0.051662713,0.256333,0.026641013,0.64728624],"study_design_scores_gemma":[0.0018105579,0.001493085,0.0015715288,0.00007089534,0.00005081166,0.000029967714,0.0016458188,0.840247,0.0023941547,0.14472173,0.005383636,0.00058084755],"about_ca_topic_score_codex":0.0000109879875,"about_ca_topic_score_gemma":0.000008711402,"teacher_disagreement_score":0.82819057,"about_ca_system_score_codex":0.00003962933,"about_ca_system_score_gemma":0.0000794345,"threshold_uncertainty_score":0.6469754},"labels":[],"label_agreement":null},{"id":"W4386546822","doi":"10.1007/s00362-023-01471-8","title":"Kendall’s tau-based inference for gradually changing dependence structures","year":2023,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Methods and Inference","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":"Université du Québec à Trois-Rivières; Université de Sherbrooke","funders":"","keywords":"Estimator; Bivariate analysis; Mathematics; Series (stratigraphy); Statistics; Joint probability distribution; Combinatorics; Geology","score_opus":0.10276642007201828,"score_gpt":0.4127067413320207,"score_spread":0.30994032126000237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386546822","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":[0.0035499039,0.000009058472,0.99051833,0.00035771925,0.00032906837,0.00047097044,0.0010396944,0.00033517982,0.0033900829],"genre_scores_gemma":[0.4464497,0.0000053321924,0.5526593,0.00031520744,0.00007553478,0.00011787145,0.0000661988,0.00003836987,0.00027249675],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99780595,0.00012618718,0.00040099933,0.0004625157,0.0004452448,0.0007591041],"domain_scores_gemma":[0.986901,0.012336818,0.00009429211,0.00029790596,0.00013394466,0.00023607795],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00062850385,0.00025853238,0.00036881363,0.00016088854,0.00023629243,0.00007679319,0.00027946793,0.000109928864,0.0007997359],"category_scores_gemma":[0.01696714,0.00021892787,0.0000778555,0.000430846,0.00022068694,0.000043082193,0.00007606684,0.00021354783,0.0000605299],"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":[0.000042316875,0.000022377662,0.00015034998,0.00023287516,0.000021171001,0.00002413483,0.0001439855,0.000028524875,0.0007689116,0.95777506,0.0024677492,0.03832257],"study_design_scores_gemma":[0.0005198918,0.00020366523,0.0052680233,0.000060809256,0.00005484449,0.0000020672962,0.00020925936,0.017169584,0.00043918227,0.974547,0.00116784,0.00035781978],"about_ca_topic_score_codex":0.000015898242,"about_ca_topic_score_gemma":0.000024853134,"teacher_disagreement_score":0.4428998,"about_ca_system_score_codex":0.000041768206,"about_ca_system_score_gemma":0.00013181203,"threshold_uncertainty_score":0.99131334},"labels":[],"label_agreement":null},{"id":"W4390750711","doi":"10.1007/s00362-023-01524-y","title":"Deficiency bounds for the multivariate inverse hypergeometric distribution","year":2024,"lang":"en","type":"article","venue":"Statistical Papers","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":"Université de Montréal; McGill University","funders":"","keywords":"Multivariate statistics; Mathematics; Hypergeometric distribution; Multinomial distribution; Multivariate normal distribution; Statistics; Inverse; Covariance; Population; Bivariate analysis; Applied mathematics; Combinatorics; Medicine","score_opus":0.07017648119283712,"score_gpt":0.38332331341468967,"score_spread":0.3131468322218526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390750711","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":[0.00022324084,0.00009354328,0.98726714,0.0015897163,0.0002931224,0.00051175454,0.00658536,0.00021963278,0.0032165179],"genre_scores_gemma":[0.9656664,0.00001939826,0.031768903,0.0001800455,0.000092258146,0.00040213225,0.0010107441,0.000026604659,0.00083349814],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99877197,0.000039191018,0.00032508696,0.00029542256,0.00026529527,0.00030300935],"domain_scores_gemma":[0.99221087,0.0073097544,0.000037585865,0.00021697354,0.00009935279,0.00012545119],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034989146,0.00014682251,0.00014148011,0.000048581438,0.00039072707,0.00015403505,0.0001534727,0.00006422333,0.0008894559],"category_scores_gemma":[0.0055357036,0.00009943261,0.00008455059,0.0006669246,0.00024585938,0.000058281432,0.00002858968,0.00015539039,0.00022977055],"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":[0.0000095634505,0.000055749282,0.0000043358355,0.000090231064,0.000021662281,0.0000018656355,0.0000383494,0.000013239928,0.00012349678,0.9329878,0.048204616,0.018449062],"study_design_scores_gemma":[0.00041820394,0.00007593334,0.004660582,0.00003298325,0.00027565533,0.0000098977325,0.00020254012,0.20313565,0.000037011785,0.6152558,0.17560838,0.000287352],"about_ca_topic_score_codex":0.00002022634,"about_ca_topic_score_gemma":0.000008733029,"teacher_disagreement_score":0.9654432,"about_ca_system_score_codex":0.0001240761,"about_ca_system_score_gemma":0.00008063436,"threshold_uncertainty_score":0.9738918},"labels":[],"label_agreement":null},{"id":"W4393308845","doi":"10.1007/s00362-024-01534-4","title":"Bootstrapping generalized linear models to accommodate overdispersed count data","year":2024,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","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":"University of Alberta; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bootstrapping (finance); Count data; Generalized linear model; Computer science; Econometrics; Statistics; Mathematics; Poisson distribution","score_opus":0.19405983639474508,"score_gpt":0.42972403172365853,"score_spread":0.23566419532891345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393308845","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":[0.00028369608,0.00006507309,0.9745283,0.00070163806,0.00039035353,0.000326372,0.003815723,0.00025003197,0.019638788],"genre_scores_gemma":[0.088897675,0.000027968179,0.9095764,0.00072990166,0.00021645728,0.000029998217,0.00019648855,0.000063964384,0.0002611025],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975609,0.00016616457,0.0004972073,0.00076248473,0.00048512948,0.00052811496],"domain_scores_gemma":[0.9957858,0.002883481,0.00003403589,0.00086661684,0.000054395823,0.0003757029],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006184966,0.00028287026,0.0004325392,0.000085514796,0.00011546287,0.0002059026,0.00054657384,0.0001012416,0.0017217479],"category_scores_gemma":[0.0014399212,0.00023206402,0.000054576853,0.00027160026,0.00013527254,0.00019075879,0.00031203192,0.00031602551,0.0002221855],"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":[0.000039863364,0.00003799847,0.0000027788822,0.00019744983,0.000076866,0.00012187521,0.0001906446,0.000033412984,0.0008790681,0.9473836,0.018329782,0.032706656],"study_design_scores_gemma":[0.00020071666,0.00005569146,0.000054607634,0.00014330636,0.000101857855,0.000009052023,0.00008147266,0.28959098,0.00002839637,0.6952755,0.014139575,0.0003188964],"about_ca_topic_score_codex":0.000097630975,"about_ca_topic_score_gemma":0.000035380886,"teacher_disagreement_score":0.28955755,"about_ca_system_score_codex":0.00007526141,"about_ca_system_score_gemma":0.00013133118,"threshold_uncertainty_score":0.9991908},"labels":[],"label_agreement":null},{"id":"W4396706555","doi":"10.1007/s00362-024-01558-w","title":"Multivariate stochastic comparisons of sequential order statistics with non-identical components","year":2024,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Statistical Distribution Estimation and Applications","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":"McMaster University","funders":"","keywords":"Multivariate statistics; Statistics; Order statistic; Multivariate analysis; Mathematics; Order (exchange); Computer science; Econometrics; Economics","score_opus":0.0599202542341342,"score_gpt":0.37594774896662747,"score_spread":0.31602749473249325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396706555","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":[0.0012650368,0.0000103700295,0.9884636,0.00021918157,0.00015980552,0.0004241314,0.006703427,0.00015291673,0.0026015227],"genre_scores_gemma":[0.7175631,0.000001124649,0.2814618,0.000034303423,0.000030735002,0.000050335264,0.0006208501,0.000034820416,0.00020291134],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978257,0.00008385449,0.0007052343,0.00040966034,0.00059537834,0.00038019774],"domain_scores_gemma":[0.99632335,0.0027710984,0.00010531082,0.0002744945,0.00024716972,0.00027858396],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001952337,0.00026196265,0.00042497116,0.00009125681,0.00013520912,0.000090874215,0.00016987589,0.00008714484,0.0021835337],"category_scores_gemma":[0.0010947774,0.00021404751,0.000048601887,0.0004057983,0.00060753163,0.000066196386,0.000055067958,0.00030124534,0.0002545816],"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":[0.00006594606,0.00026791377,0.000022690167,0.00029275534,0.00014172363,0.000034274377,0.00010521077,0.00019590955,0.0013240378,0.98641473,0.010052677,0.0010821499],"study_design_scores_gemma":[0.0022382743,0.00039371545,0.018099414,0.0005388969,0.0010575849,0.00006401125,0.0003131271,0.71261626,0.00020530346,0.26102623,0.002519313,0.00092783687],"about_ca_topic_score_codex":0.000070613256,"about_ca_topic_score_gemma":0.000025827027,"teacher_disagreement_score":0.72538847,"about_ca_system_score_codex":0.000082987855,"about_ca_system_score_gemma":0.00016530318,"threshold_uncertainty_score":0.99872863},"labels":[],"label_agreement":null},{"id":"W4396800896","doi":"10.1007/s00362-024-01561-1","title":"Variation comparison between infinitely divisible distributions and the normal distribution","year":2024,"lang":"en","type":"article","venue":"Statistical Papers","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":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Variation (astronomy); Distribution (mathematics); Mathematics; Infinite divisibility; Statistics; Statistical physics; Mathematical analysis; Physics; Astrophysics","score_opus":0.016315451939615404,"score_gpt":0.29549111378229215,"score_spread":0.2791756618426767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396800896","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":[0.00023896692,0.00020932515,0.99303573,0.0026586016,0.00021665642,0.00013194315,0.00047355203,0.000119395176,0.0029158518],"genre_scores_gemma":[0.87733877,0.000016647567,0.12224444,0.000070213144,0.00008473321,0.000014898045,0.00017471735,0.000004669171,0.000050934672],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99885565,0.00021784625,0.00023060085,0.0002769162,0.00019859885,0.00022040616],"domain_scores_gemma":[0.99816537,0.0014758037,0.000028943821,0.0001969217,0.000029216466,0.000103763676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063543994,0.00010926042,0.00016716756,0.000023194643,0.00023518979,0.0003845812,0.00020606509,0.000056823555,0.000021628235],"category_scores_gemma":[0.00024042037,0.00007135956,0.00003840851,0.00027908254,0.00020773444,0.000194729,0.00012078874,0.00023097884,0.000022254295],"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":[0.0000045892893,0.0000065071295,0.00015105832,0.000013627812,0.00001791222,0.0000025551415,0.00022098426,0.0000020568252,0.000017729737,0.861248,0.0005935456,0.13772143],"study_design_scores_gemma":[0.0006695496,0.000084616935,0.17371419,0.000043222684,0.00012122751,0.000011204147,0.000017492599,0.21107525,0.000042596643,0.590726,0.023206556,0.00028807137],"about_ca_topic_score_codex":0.000050383827,"about_ca_topic_score_gemma":0.000003970646,"teacher_disagreement_score":0.87709975,"about_ca_system_score_codex":0.000040118863,"about_ca_system_score_gemma":0.00005075018,"threshold_uncertainty_score":0.37085253},"labels":[],"label_agreement":null},{"id":"W4399385611","doi":"10.1007/s00362-024-01574-w","title":"Generalized simulated method-of-moments estimators for multivariate copulas","year":2024,"lang":"en","type":"article","venue":"Statistical Papers","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":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multivariate statistics; Estimator; Mathematics; Copula (linguistics); Statistics; Econometrics; Generalized method of moments; Multivariate analysis; Method of moments (probability theory); Applied mathematics","score_opus":0.05481795993373654,"score_gpt":0.3414203320694396,"score_spread":0.28660237213570305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399385611","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":[0.022152053,0.00061716547,0.9718299,0.000114862494,0.00069845223,0.00032732598,0.0019308461,0.00006911075,0.0022603099],"genre_scores_gemma":[0.76360357,0.000026091024,0.23576313,0.000056299814,0.0000444944,0.000016969463,0.000090445756,0.00003090994,0.00036811983],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986448,0.00001908373,0.0006253977,0.00039844468,0.000041164054,0.00027110003],"domain_scores_gemma":[0.9990952,0.00055134646,0.000082877596,0.00015367409,0.000029394057,0.00008749708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048792284,0.0001414665,0.0004052298,0.00011734388,0.00006661539,0.00004203644,0.00009883079,0.00009744731,0.00033374986],"category_scores_gemma":[0.0007389797,0.00014839336,0.0001158495,0.00017143975,0.00005251407,0.00007166336,0.000025788748,0.000103551676,0.00007840102],"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":[0.000075061515,0.000040772284,0.0010286134,0.00019608175,0.00008742536,0.0000042351676,0.00028665204,0.0051566116,0.00032626538,0.98098034,0.0004217135,0.011396255],"study_design_scores_gemma":[0.0005132684,0.00006769591,0.0016604759,0.000031691176,0.00002074776,4.765845e-7,0.0000108256545,0.8029027,0.000075880635,0.17664188,0.017894816,0.0001795683],"about_ca_topic_score_codex":0.0005397553,"about_ca_topic_score_gemma":0.000007978439,"teacher_disagreement_score":0.80433846,"about_ca_system_score_codex":0.000062076804,"about_ca_system_score_gemma":0.000030104862,"threshold_uncertainty_score":0.60513055},"labels":[],"label_agreement":null},{"id":"W4405190282","doi":"10.1007/s00362-024-01622-5","title":"Inference for the normal coefficient of variation: an approximate marginal likelihood approach","year":2024,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","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 British Columbia, Okanagan Campus; University of British Columbia; York University","funders":"","keywords":"Inference; Statistics; Coefficient of variation; Variation (astronomy); Mathematics; Maximum likelihood; Econometrics; Computer science; Artificial intelligence","score_opus":0.07310450964918976,"score_gpt":0.40761632618642185,"score_spread":0.3345118165372321,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405190282","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":[0.00024452872,0.00017007998,0.991862,0.00019446228,0.0005782052,0.0003711985,0.0006490246,0.000060970473,0.0058695083],"genre_scores_gemma":[0.83375555,0.0000059231556,0.16571547,0.000045139674,0.00015192552,0.00008510324,0.00002495791,0.00001811713,0.00019780957],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969419,0.00011645319,0.000661642,0.0006194578,0.0012438365,0.00041667392],"domain_scores_gemma":[0.9873814,0.011591254,0.000103242535,0.00042103825,0.00031387262,0.00018920455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017551858,0.00017936275,0.00027760552,0.000094148134,0.00024078785,0.00030311887,0.0006374192,0.00006349443,0.0003597323],"category_scores_gemma":[0.006583451,0.00010751545,0.000066600354,0.00057876884,0.0004052836,0.00026109852,0.000102323174,0.0002302011,0.000041764575],"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":[0.00012277294,0.00011049192,0.000095712654,0.00013735703,0.000032123608,0.0000067482842,0.00093339663,0.00699281,0.00048865314,0.7715321,0.0004149467,0.21913289],"study_design_scores_gemma":[0.0002807507,0.00029168004,0.005144172,0.000027360331,0.000067974295,0.000006342135,0.0009606445,0.77594984,0.00008987201,0.21118228,0.0057706716,0.0002284059],"about_ca_topic_score_codex":0.0000145629,"about_ca_topic_score_gemma":0.000004520708,"teacher_disagreement_score":0.83351105,"about_ca_system_score_codex":0.00004535237,"about_ca_system_score_gemma":0.00016691312,"threshold_uncertainty_score":0.7881481},"labels":[],"label_agreement":null},{"id":"W4407241250","doi":"10.1007/s00362-025-01668-z","title":"The empirical Bernstein process with application to uniformity testing","year":2025,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Control Systems and Identification","field":"Engineering","cited_by":0,"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","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Process (computing); Computer science; Psychology; Mathematics; Programming language","score_opus":0.015086513723617292,"score_gpt":0.2729147196690699,"score_spread":0.2578282059454526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407241250","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":[0.08018593,0.00009675027,0.8130417,0.0015348119,0.00024613837,0.0011591985,0.00004449401,0.000443798,0.103247195],"genre_scores_gemma":[0.99866444,9.235509e-7,0.0007839947,0.000060969996,0.000027089,0.0001382979,0.0000070403544,0.000008580708,0.00030864],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99943626,0.000012951225,0.00015417121,0.00012812008,0.00011708023,0.00015141428],"domain_scores_gemma":[0.9994374,0.00027924273,0.000013213869,0.00015280905,0.00006159763,0.000055733362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011899478,0.000073022464,0.00007931563,0.0000220222,0.00013986733,0.00006159937,0.00009400272,0.00002562437,0.0000038824905],"category_scores_gemma":[0.00020077024,0.000048285772,0.00000843786,0.0002726044,0.000031221793,0.00002815376,0.000008744631,0.000078112316,0.000029653895],"study_design_candidate":"design_other","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":[0.00011666086,0.00005362717,0.022960389,0.0004671616,0.0001394593,0.000004518502,0.0006314206,0.023972066,0.013389802,0.097559415,0.008312775,0.8323927],"study_design_scores_gemma":[0.00097380806,0.00015315713,0.54371065,0.00020188197,0.00011019349,0.0000069791417,0.0011509794,0.32639775,0.0006164908,0.007886016,0.11817383,0.00061825267],"about_ca_topic_score_codex":0.000038198606,"about_ca_topic_score_gemma":0.00027442587,"teacher_disagreement_score":0.91847855,"about_ca_system_score_codex":0.00005711406,"about_ca_system_score_gemma":0.000027102406,"threshold_uncertainty_score":0.19690366},"labels":[],"label_agreement":null},{"id":"W4409184329","doi":"10.1007/s00362-025-01691-0","title":"Forecasting natural disaster frequencies using nonstationary count time series models","year":2025,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University","funders":"Institut Louis Bachelier; Natural Sciences and Engineering Research Council of Canada; Université d'Orléans","keywords":"Series (stratigraphy); Natural disaster; Time series; Computer science; Econometrics; Meteorology; Geography; Mathematics; Geology; Machine learning","score_opus":0.04153104364193647,"score_gpt":0.2435630750453514,"score_spread":0.20203203140341494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409184329","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":[0.24204063,0.0019942066,0.6124754,0.0005981807,0.0010394892,0.0004165344,0.0019422616,0.00011041886,0.1393829],"genre_scores_gemma":[0.9547567,0.00002033221,0.0435318,0.00026304825,0.00004284726,0.000008498932,0.00006466162,0.000014833437,0.0012973014],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880844,0.000013892796,0.0004903151,0.00033693045,0.000050669012,0.00029971942],"domain_scores_gemma":[0.99946684,0.00019203922,0.00009304044,0.00015189419,0.000046989266,0.000049211136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022007717,0.00014906001,0.00029374452,0.00010772948,0.00023046072,0.00007240148,0.00010981324,0.0000704465,0.00022619647],"category_scores_gemma":[0.00033045516,0.00016474239,0.00005966284,0.00017046354,0.0001577796,0.0003590278,0.000052422165,0.00016351996,0.00005725133],"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":[0.000055313725,0.000027945565,0.003074532,0.00006438304,0.000037020975,0.0000091994425,0.00057666673,0.0064213346,0.00013891475,0.9867711,0.0003715894,0.0024519842],"study_design_scores_gemma":[0.00015528123,0.000016912996,0.0012722145,0.000033866836,0.0000081299,0.0000023341406,0.00013282581,0.6862519,0.00000550342,0.3110649,0.0008922102,0.00016391961],"about_ca_topic_score_codex":0.0002547738,"about_ca_topic_score_gemma":0.00003675707,"teacher_disagreement_score":0.71271604,"about_ca_system_score_codex":0.000147907,"about_ca_system_score_gemma":0.00006239963,"threshold_uncertainty_score":0.6718},"labels":[],"label_agreement":null},{"id":"W4409864150","doi":"10.1007/s00362-025-01703-z","title":"Tweedie compound Poisson multivariate state space models for semicontinuous time series","year":2025,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"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 New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; Guizhou Science and Technology Department; National Natural Science Foundation of China","keywords":"Series (stratigraphy); Multivariate statistics; Poisson distribution; State space; Mathematics; State (computer science); Applied mathematics; Statistics; Algorithm; Geology","score_opus":0.013786287884235013,"score_gpt":0.2692750769097881,"score_spread":0.25548878902555305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409864150","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":[0.0005178696,0.000056926612,0.9840923,0.0020272105,0.00026849343,0.00025300487,0.00016383883,0.0002288493,0.01239153],"genre_scores_gemma":[0.5331343,0.000015515883,0.45760095,0.0007180714,0.000034280165,0.00004649279,0.000032895387,0.000018071016,0.008399453],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99850756,0.0000646963,0.00028007355,0.000505128,0.00018308891,0.0004594339],"domain_scores_gemma":[0.99880314,0.0005236992,0.00005748259,0.0003397457,0.00013341513,0.00014249903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023744367,0.00020664847,0.00028811945,0.00006500453,0.00018497682,0.00022332491,0.00047413,0.00007295165,0.000016664433],"category_scores_gemma":[0.00015110639,0.0001916027,0.000055794837,0.00018122474,0.00012644996,0.0002945451,0.00014946693,0.00016270133,0.000043345222],"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":[0.0000706957,0.000049271526,0.000008858003,0.000051024632,0.00005014188,0.000014211338,0.0003870614,0.0023137834,0.006286231,0.96272194,0.004682906,0.023363877],"study_design_scores_gemma":[0.00045076813,0.00010916163,0.00015443844,0.000051182225,0.000018319537,0.0000033222411,0.000022072189,0.6224636,0.00036628547,0.37331852,0.0028079844,0.00023435421],"about_ca_topic_score_codex":0.000114178525,"about_ca_topic_score_gemma":0.000016293374,"teacher_disagreement_score":0.6201498,"about_ca_system_score_codex":0.0000559662,"about_ca_system_score_gemma":0.00014759562,"threshold_uncertainty_score":0.78133315},"labels":[],"label_agreement":null},{"id":"W4410381351","doi":"10.1007/s00362-025-01708-8","title":"Local linear smoothing for regression surfaces on the simplex using Dirichlet kernels","year":2025,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Alliance de recherche numérique du Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Smoothing; Mathematics; Linear regression; Simplex; Regression; Dirichlet distribution; Statistics; Mathematical analysis; Combinatorics","score_opus":0.020941776305921783,"score_gpt":0.3220951516595378,"score_spread":0.30115337535361597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410381351","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":[0.004612862,0.00007296727,0.99160534,0.00034563226,0.00007187092,0.00020729558,0.00006173645,0.00028652707,0.0027357754],"genre_scores_gemma":[0.9167348,0.00002184739,0.082553595,0.00046123908,0.000027258067,0.000026538732,0.00001702973,0.000027983806,0.00012969406],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991145,0.000037299535,0.0002232681,0.00020479567,0.00015358932,0.00026651903],"domain_scores_gemma":[0.9982743,0.0014212902,0.000024917528,0.00019374958,0.000030770247,0.00005492325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013273601,0.0001649681,0.00021791516,0.000046895082,0.00014881506,0.00002324653,0.00014646999,0.00006742774,0.000080756836],"category_scores_gemma":[0.00041489757,0.00010513685,0.000064726904,0.00022826444,0.0001370998,0.000039099483,0.000033839708,0.00020120865,0.000006349196],"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":[0.00016763798,0.00008881577,0.00014239673,0.00033751095,0.00031648966,0.000021277316,0.00017973926,0.4680476,0.03789806,0.19994256,0.016085442,0.27677247],"study_design_scores_gemma":[0.00016967248,0.000052794006,0.00021433936,0.00014153618,0.000071524344,4.4386871e-7,0.0001603047,0.91834253,0.008380443,0.020342566,0.05187505,0.0002487871],"about_ca_topic_score_codex":0.000017496735,"about_ca_topic_score_gemma":0.000005402044,"teacher_disagreement_score":0.91212195,"about_ca_system_score_codex":0.000104976316,"about_ca_system_score_gemma":0.000012203871,"threshold_uncertainty_score":0.42873564},"labels":[],"label_agreement":null},{"id":"W4411990884","doi":"10.1007/s00362-025-01723-9","title":"Handling skewness and directional tails in model-based clustering","year":2025,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University","funders":"Natural Sciences and Engineering Research Council of Canada; European Commission; National Science Foundation","keywords":"Skewness; Cluster analysis; Computer science; Econometrics; Statistics; Statistical physics; Mathematics; Artificial intelligence; Physics","score_opus":0.00959192071079757,"score_gpt":0.28385415082257015,"score_spread":0.2742622301117726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411990884","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":[0.00028470682,0.000064515916,0.98947424,0.0005291578,0.00014223563,0.000069669455,0.000006149955,0.00003913688,0.009390193],"genre_scores_gemma":[0.37412328,0.0000034007205,0.6252707,0.00044403353,0.000006874837,0.000009198111,0.0000010857277,0.000002650352,0.0001387866],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922127,0.00006654416,0.00014233713,0.00028738062,0.00009859212,0.00018385971],"domain_scores_gemma":[0.999444,0.000327886,0.000014799092,0.00013240622,0.000018525852,0.000062398954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002506472,0.000085906846,0.00013043704,0.00008527489,0.000073426265,0.00007182678,0.00013700959,0.0000452834,0.000004979004],"category_scores_gemma":[0.00010610739,0.00007895251,0.000015900989,0.00017267784,0.000058322632,0.00007375132,0.00007532726,0.00011807156,8.829679e-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":[0.000014340509,0.000023102211,0.00020519854,0.0000459479,0.0000053949057,0.000012829793,0.000090057765,0.0048398827,0.00096391997,0.74079263,0.000049851165,0.25295684],"study_design_scores_gemma":[0.00026791968,0.000009720783,0.0016877137,0.000039165032,0.0000031596185,9.858351e-7,0.000003009688,0.85066783,0.000107477776,0.14698264,0.00014832651,0.00008207167],"about_ca_topic_score_codex":0.000021322245,"about_ca_topic_score_gemma":0.000046634865,"teacher_disagreement_score":0.84582794,"about_ca_system_score_codex":0.000032594307,"about_ca_system_score_gemma":0.000086260436,"threshold_uncertainty_score":0.321959},"labels":[],"label_agreement":null},{"id":"W4413661374","doi":"10.1007/s00362-025-01731-9","title":"Correction: Tweedie compound Poisson multivariate state space models for semicontinuous time series","year":2025,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Bayesian Modeling and Causal Inference","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 New Brunswick","funders":"","keywords":"Series (stratigraphy); Multivariate statistics; Poisson distribution; State space; Applied mathematics; Time series; Mathematics; Statistics; Computer science; Geology","score_opus":0.013113843981462703,"score_gpt":0.2665062343926641,"score_spread":0.2533923904112014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413661374","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":[0.00023208816,0.00004699624,0.97823775,0.0015557938,0.0010669545,0.00023339278,0.000090955815,0.00025716017,0.01827894],"genre_scores_gemma":[0.6002295,0.000022398079,0.3677172,0.0008578496,0.00007569323,0.000071270566,0.000045066954,0.000024374844,0.030956615],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859524,0.000065836706,0.00027110352,0.00049065513,0.0001747886,0.00040238805],"domain_scores_gemma":[0.9987357,0.00061708456,0.00006032454,0.00030362062,0.00015321135,0.0001300074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002151572,0.00019765297,0.00026966952,0.0000651012,0.00022271533,0.00022366479,0.00037608042,0.00007407024,0.000021007612],"category_scores_gemma":[0.00017983325,0.0001874891,0.0000545826,0.0002087255,0.00011768493,0.00029782858,0.00011802506,0.00018314435,0.000041617608],"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":[0.00014544449,0.00008704091,0.000018368366,0.000060871396,0.00008274807,0.000020030377,0.0006562095,0.0070829405,0.0050833793,0.8948823,0.034188733,0.057691924],"study_design_scores_gemma":[0.00040035206,0.00012885618,0.0001902525,0.00006167254,0.000019021896,0.0000068900395,0.000031378742,0.81654066,0.00035901446,0.17790647,0.004127392,0.00022800658],"about_ca_topic_score_codex":0.00013622858,"about_ca_topic_score_gemma":0.000024122564,"teacher_disagreement_score":0.8094577,"about_ca_system_score_codex":0.00006897539,"about_ca_system_score_gemma":0.00015426551,"threshold_uncertainty_score":0.7645584},"labels":[],"label_agreement":null},{"id":"W4415494756","doi":"10.1007/s00362-025-01761-3","title":"An efficient hybrid approach of quantile and expectile regression","year":2025,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"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 Montréal","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada","keywords":"Quantile; Quantile regression; Estimator; Robustness (evolution); Outlier; Regression; Linear regression; Least absolute deviations","score_opus":0.054361407965509416,"score_gpt":0.4263557487580963,"score_spread":0.37199434079258686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415494756","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":[0.015171933,0.00006635172,0.96493167,0.000023182827,0.00006795045,0.00019308072,0.00016616307,0.000040636984,0.01933904],"genre_scores_gemma":[0.48329332,0.0000057760417,0.5165368,0.000024463461,0.000006783877,0.000011643289,0.000007589442,0.000008447735,0.000105184496],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998837,0.00013967238,0.00030169493,0.00032687097,0.00018450906,0.00021027672],"domain_scores_gemma":[0.9979829,0.0015186986,0.00006404196,0.00026084375,0.000050845832,0.00012262714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025146166,0.00013829969,0.00032712816,0.000054228865,0.000083777726,0.000012729218,0.000089665446,0.000044669763,0.00007374686],"category_scores_gemma":[0.001292325,0.000104235085,0.000027488833,0.00008829778,0.00025234796,0.00002503407,0.000046147576,0.00012560851,7.998299e-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":[0.00006926318,0.00022606344,0.00002276348,0.00021660287,0.000014294636,0.000005530402,0.00013821622,0.00007908925,0.0026602389,0.9633285,0.00040261456,0.03283684],"study_design_scores_gemma":[0.00068033586,0.0002244678,0.00063239323,0.0001314942,0.000088693814,0.0000058456744,0.00091260026,0.10373422,0.0021127162,0.8907777,0.0004603271,0.00023917803],"about_ca_topic_score_codex":0.000009437654,"about_ca_topic_score_gemma":0.0000010945298,"teacher_disagreement_score":0.46812138,"about_ca_system_score_codex":0.000018943047,"about_ca_system_score_gemma":0.000028197877,"threshold_uncertainty_score":0.42505834},"labels":[],"label_agreement":null},{"id":"W4416411423","doi":"10.1007/s00362-025-01775-x","title":"Generalized FGM dependence: geometrical representation and convex bounds on sums","year":2025,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Ministero dell’Istruzione, dell’Università e della Ricerca; Politecnico di Torino","keywords":"Bernoulli's principle; Regular polygon; Multivariate statistics; Independent and identically distributed random variables; Class (philosophy); Copula (linguistics); Representation (politics); Aggregate (composite); Bernoulli distribution","score_opus":0.05833186546979928,"score_gpt":0.4156883007651458,"score_spread":0.3573564352953465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416411423","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":[0.29625195,0.00047112373,0.4114623,0.0042940006,0.0019353504,0.00084877963,0.00023722877,0.00015955376,0.2843397],"genre_scores_gemma":[0.9827697,0.0003585336,0.0076625445,0.001086886,0.000043210162,0.000014481311,0.000041503547,0.0000073985657,0.008015743],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99762315,0.00021836045,0.0004937617,0.0005249033,0.00091861165,0.0002212146],"domain_scores_gemma":[0.99650156,0.0027954841,0.000091146256,0.00031271426,0.00014844717,0.00015065864],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008124982,0.00012239408,0.00026143325,0.0003953621,0.000198354,0.00030030232,0.0002017051,0.00009720937,0.00093720894],"category_scores_gemma":[0.0068222326,0.00009154058,0.000043041815,0.0012485731,0.00022355332,0.00011933235,0.00006018694,0.00013805773,0.00013152033],"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":[0.00031782396,0.000087406755,0.046721816,0.000007039814,0.000047723654,0.000054870405,0.00018716493,0.0012886004,0.00030044199,0.675286,0.048151284,0.22754984],"study_design_scores_gemma":[0.0025978344,0.00035331983,0.5229049,0.000031105523,0.00009827961,0.000015428597,0.0007853569,0.044485603,0.00042566436,0.34638628,0.08139071,0.0005255525],"about_ca_topic_score_codex":0.00011049292,"about_ca_topic_score_gemma":0.000025541929,"teacher_disagreement_score":0.6865178,"about_ca_system_score_codex":0.00003464673,"about_ca_system_score_gemma":0.00007751874,"threshold_uncertainty_score":0.9999761},"labels":[],"label_agreement":null},{"id":"W630834592","doi":"10.1007/s00362-015-0697-8","title":"Some results on the relative ordering of two frailty models","year":2015,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":24,"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 Alberta","funders":"Deanship of Scientific Research, King Saud University; Natural Sciences and Engineering Research Council of Canada","keywords":"Residual; Statistics; Variable (mathematics); Hazard; Hazard ratio; Econometrics; Mathematics; Gerontology; Computer science; Medicine; Algorithm; Confidence interval; Chemistry","score_opus":0.09574594065934255,"score_gpt":0.3560232538766365,"score_spread":0.26027731321729397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W630834592","genre_codex":"other","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":[0.04688248,0.00007978418,0.006831372,0.0037768509,0.0005659996,0.0006284312,0.00030835002,0.00009095532,0.9408358],"genre_scores_gemma":[0.9965741,0.000031942356,0.00230455,0.00034348102,0.00011010846,0.000015257884,0.0000072933935,0.000009842354,0.00060343643],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980749,0.00035973196,0.00027143196,0.0002391246,0.00075266516,0.0003021862],"domain_scores_gemma":[0.9985986,0.0008134233,0.00010032374,0.0002447169,0.00010287013,0.00014012003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013386095,0.00010758644,0.00015969883,0.00004475978,0.00024210775,0.00003202628,0.00025461623,0.000046681474,0.000051724714],"category_scores_gemma":[0.0012806609,0.00007780506,0.000052590938,0.00024251296,0.0007697286,0.00015728382,0.00005222891,0.00018361952,0.000043172346],"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":[0.00006395936,0.000037905425,0.00021549372,0.00000435914,0.000035433175,0.000005914838,0.0055009797,0.0010846768,0.0000057162433,0.9888769,0.0024369243,0.0017317671],"study_design_scores_gemma":[0.00086373993,0.000142552,0.0057879705,0.000033973873,0.00004096648,1.1701067e-7,0.0055738594,0.0015031876,0.000017369543,0.97354126,0.01228081,0.00021416796],"about_ca_topic_score_codex":0.0026871555,"about_ca_topic_score_gemma":0.0011523452,"teacher_disagreement_score":0.9496916,"about_ca_system_score_codex":0.000075657284,"about_ca_system_score_gemma":0.00008783812,"threshold_uncertainty_score":0.4062193},"labels":[],"label_agreement":null}]}