{"meta":{"query_hash":"13caac3b070d","filters":{"venue":"Journal of Statistical Theory and Applications"},"cohort_total":11,"direct_labels_cover":0,"predictions_cover":11,"exported":11,"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/13caac3b070d","api":"https://metacan.xera.ac/api/v1/cohort?venue=Journal+of+Statistical+Theory+and+Applications"},"results":[{"id":"W2561056165","doi":"10.2991/jsta.2016.15.4.8","title":"Shrinkage Estimation of Linear Regression Models with GARCH Errors","year":2016,"lang":"en","type":"article","venue":"Journal of Statistical Theory and Applications","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":4,"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 Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Shrinkage; Mathematics; Linear regression; Statistics; Autoregressive conditional heteroskedasticity; Estimation; Regression; Regression analysis; Econometrics; Volatility (finance); Economics","score_opus":0.009961429023289453,"score_gpt":0.28074745818071506,"score_spread":0.2707860291574256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2561056165","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02548404,0.00020284245,0.9734903,0.00010863485,0.000020801594,0.000017322085,0.000034491422,0.00016102789,0.000480489],"genre_scores_gemma":[0.7307866,0.00090910087,0.26481974,0.00012692367,0.00017245492,0.0001796604,0.0004184782,0.00019216897,0.0023948625],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99726284,0.0015643456,0.000116188225,0.00030386224,0.0006280115,0.00012477404],"domain_scores_gemma":[0.99032587,0.0070013194,0.00096099096,0.00081634463,0.0008091838,0.000086290216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006010959,0.00070828124,0.001315632,0.0009506353,0.00029112486,0.000784519,0.0010588524,0.0009366437,0.00075571955],"category_scores_gemma":[0.026831143,0.0005460732,0.00092669023,0.0010153344,0.0008734339,0.001491496,0.0016967756,0.0016074276,0.00022810049],"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":[0.00009213634,0.000059062706,0.007179888,0.00017343575,0.00018134183,0.00017441255,0.00019929463,0.7853695,0.004416121,0.065663844,0.0011933431,0.13529757],"study_design_scores_gemma":[0.000009521813,0.000026074655,0.000902749,0.000013890988,0.000015392017,0.000031731175,0.000014396813,0.9682712,0.0010693708,0.028892957,0.0007365862,0.000016077234],"about_ca_topic_score_codex":0.0012094894,"about_ca_topic_score_gemma":0.00086889626,"teacher_disagreement_score":0.006010959,"about_ca_system_score_codex":0.00038772775,"about_ca_system_score_gemma":0.0005770579,"threshold_uncertainty_score":0.031789422},"labels":[],"label_agreement":null},{"id":"W2668123086","doi":"10.2991/jsta.2017.16.1.8","title":"Optimal Structure (ligkl/ig) Designs for Comparing Test Treatments with a Control","year":2017,"lang":"en","type":"article","venue":"Journal of Statistical Theory and Applications","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","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 Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Test (biology); Statistics; Econometrics; Reliability engineering; Engineering","score_opus":0.07329674452216214,"score_gpt":0.36919011024548315,"score_spread":0.29589336572332103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2668123086","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017624483,0.00021099907,0.978639,0.00013360904,0.00006546677,0.0013044549,0.00023759081,0.00040459255,0.0013798091],"genre_scores_gemma":[0.15034525,0.00014327277,0.84147376,0.00026177437,0.00006578324,0.0066196714,0.00030390304,0.00009002657,0.00069651555],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.8826257,0.09246326,0.002994326,0.011057089,0.008954995,0.0019045586],"domain_scores_gemma":[0.9413267,0.038004577,0.0051198467,0.011037317,0.0037180777,0.00079357077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.066258416,0.0022215396,0.0041832253,0.0039285123,0.0012627934,0.0019096833,0.0029753041,0.0040869303,0.008440118],"category_scores_gemma":[0.10478659,0.00135065,0.0035462137,0.0024756652,0.006031189,0.003083956,0.003125514,0.0033020661,0.0013338807],"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":[0.012278197,0.0018166145,0.008559767,0.002239495,0.0016927011,0.0002913374,0.0013727769,0.06126083,0.017361196,0.5319445,0.0031083354,0.35807428],"study_design_scores_gemma":[0.0059109507,0.026969394,0.012662082,0.00053729175,0.001424053,0.00039668792,0.00038748054,0.34587184,0.02426155,0.569037,0.012026192,0.0005155355],"about_ca_topic_score_codex":0.0005568999,"about_ca_topic_score_gemma":0.00062559464,"teacher_disagreement_score":0.066258416,"about_ca_system_score_codex":0.0027823178,"about_ca_system_score_gemma":0.0032926118,"threshold_uncertainty_score":0.3504122},"labels":[],"label_agreement":null},{"id":"W2805040766","doi":"10.2991/jsta.2018.17.1.12","title":"Divergence Measures Estimation and Its Asymptotic Normality Theory Using Wavelets Empirical Processes I","year":2018,"lang":"en","type":"article","venue":"Journal of Statistical Theory and Applications","topic":"Statistical and numerical algorithms","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BP (Canada)","funders":"Centre d'Excellence africain en Mathématiques, Informatique et TIC; World Bank Group","keywords":"Mathematics; Asymptotic distribution; Econometrics; Divergence (linguistics); Local asymptotic normality; Statistics; Estimation; Wavelet; Asymptotic analysis; Applied mathematics; Normality; Estimator; Economics; Computer science; Artificial intelligence","score_opus":0.07871427853531923,"score_gpt":0.38969784792203427,"score_spread":0.310983569386715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805040766","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0077957413,0.0006763834,0.98947424,0.00030241947,0.000071264716,0.000011362256,0.000030333236,0.000043028962,0.0015953258],"genre_scores_gemma":[0.6247962,0.0052989917,0.3604967,0.00073151995,0.0011289464,0.00025712288,0.00044552863,0.00023520959,0.0066097626],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965475,0.0014882047,0.00023288207,0.00051506126,0.0010314481,0.00018493852],"domain_scores_gemma":[0.9870985,0.008915875,0.0009121091,0.0011193255,0.0016687814,0.00028540092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008203282,0.0008116907,0.0011341203,0.0024923235,0.00053156615,0.0021280553,0.0012083586,0.0014798859,0.0014397845],"category_scores_gemma":[0.03677775,0.00044372177,0.0013880441,0.0018119686,0.0039931447,0.0038789876,0.002994611,0.0034771631,0.00037463132],"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":[0.000024912302,0.000027391148,0.0013176377,0.00010636139,0.00004483069,0.00009587203,0.000121182726,0.031365365,0.0021135542,0.93619025,0.00079213246,0.02780061],"study_design_scores_gemma":[0.0000071989293,0.0000669539,0.0010631833,0.00004993455,0.000018965857,0.00022552884,0.000049994593,0.34647873,0.00130504,0.64795756,0.0027456845,0.000031103216],"about_ca_topic_score_codex":0.0007979129,"about_ca_topic_score_gemma":0.0002973486,"teacher_disagreement_score":0.008203282,"about_ca_system_score_codex":0.001306908,"about_ca_system_score_gemma":0.0011142121,"threshold_uncertainty_score":0.0433836},"labels":[],"label_agreement":null},{"id":"W2955496656","doi":"10.2991/jsta.d.190617.001","title":"A Multivariate Skew-Normal Mean-Variance Mixture Distribution and Its Application to Environmental Data with Outlying Observations","year":2019,"lang":"en","type":"article","venue":"Journal of Statistical Theory and Applications","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Statistics; Mathematics; Skew; Multivariate statistics; Multivariate analysis of variance; Variance (accounting); Multivariate normal distribution; Skew normal distribution; Kurtosis; Normal distribution; Econometrics; Computer science; Economics","score_opus":0.019402637251770067,"score_gpt":0.28406811270893545,"score_spread":0.2646654754571654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955496656","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007166869,0.0001569403,0.9919592,0.00008037083,0.000016633485,0.000038120204,0.00006513385,0.00019276631,0.0003239689],"genre_scores_gemma":[0.26139462,0.00088316767,0.73343784,0.00014055874,0.000089875175,0.00034242007,0.00085321954,0.00021942434,0.0026388867],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99773204,0.0009793063,0.00011321168,0.0005006458,0.00054275984,0.00013208122],"domain_scores_gemma":[0.99475634,0.0033303145,0.00051443663,0.00051500654,0.0007735581,0.000110408306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006097553,0.000923679,0.0012427316,0.0021601038,0.0008649444,0.0017391301,0.0019303049,0.0016352626,0.0015643738],"category_scores_gemma":[0.014773472,0.00068604294,0.0015599651,0.002895046,0.0016334535,0.0028256772,0.0018315242,0.001977744,0.0007221186],"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":[0.0002699085,0.0001178134,0.012759902,0.00034802238,0.00018932036,0.00061593915,0.0007449083,0.5767826,0.007678239,0.19741148,0.0029347327,0.20014708],"study_design_scores_gemma":[0.0000101953665,0.00003977682,0.0015450517,0.000032373875,0.0000231616,0.00024411472,0.00005119451,0.9553475,0.0012180144,0.039170794,0.002260284,0.000057616213],"about_ca_topic_score_codex":0.0049196435,"about_ca_topic_score_gemma":0.004351729,"teacher_disagreement_score":0.006097553,"about_ca_system_score_codex":0.0009622593,"about_ca_system_score_gemma":0.0013503309,"threshold_uncertainty_score":0.032247365},"labels":[],"label_agreement":null},{"id":"W3011442131","doi":"10.2991/jsta.d.200303.001","title":"Sample Design and Estimation of Parameters of Half Logistic Distribution Using Generalized Ranked-Set Sampling","year":2020,"lang":"en","type":"article","venue":"Journal of Statistical Theory and Applications","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Mathematics; Statistics; Sample (material); Logistic distribution; Sampling design; Estimation; Sampling (signal processing); Logistic regression; Computer science; Engineering","score_opus":0.2709871524496742,"score_gpt":0.42015899527755346,"score_spread":0.14917184282787926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3011442131","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011361688,0.000048974245,0.98782045,0.000020870026,0.000011341309,0.00023163058,0.00006414275,0.00008459465,0.00035620652],"genre_scores_gemma":[0.18647122,0.00016385561,0.81053567,0.000053590597,0.000020075327,0.0013242908,0.00046511967,0.00003540643,0.00093072123],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9885239,0.009065279,0.00025436963,0.0005723393,0.0013694555,0.00021463563],"domain_scores_gemma":[0.98834467,0.0074220165,0.0006044882,0.0014518409,0.0020213292,0.00015563039],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008534097,0.0006186014,0.001348793,0.0015985745,0.0005121598,0.0007740105,0.0017606852,0.0006935156,0.0030980217],"category_scores_gemma":[0.027031925,0.00048741695,0.00083098124,0.0017045764,0.0006834952,0.0009973253,0.0011514362,0.00085689384,0.00050700427],"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":[0.0011103218,0.00035821757,0.011145052,0.00087781396,0.00038451812,0.00026578843,0.00043567954,0.33289438,0.014558088,0.13288787,0.0029325737,0.5021497],"study_design_scores_gemma":[0.00015796832,0.0007745115,0.003942692,0.000068626265,0.00007430409,0.00017033811,0.00014697807,0.94233525,0.0070828605,0.04159622,0.0035836932,0.00006651079],"about_ca_topic_score_codex":0.0018599763,"about_ca_topic_score_gemma":0.0020188545,"teacher_disagreement_score":0.008534097,"about_ca_system_score_codex":0.00062848144,"about_ca_system_score_gemma":0.0014820866,"threshold_uncertainty_score":0.045133173},"labels":[],"label_agreement":null},{"id":"W3126617033","doi":"10.2991/jsta.d.210121.001","title":"Restricted Empirical Likelihood Estimation for Time Series Autoregressive Models","year":2021,"lang":"en","type":"article","venue":"Journal of Statistical Theory and Applications","topic":"Statistical Methods and Inference","field":"Mathematics","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":"University of Calgary","funders":"","keywords":"Likelihood function; Empirical likelihood; Autoregressive model; Mathematics; Series (stratigraphy); Marginal likelihood; Bayesian probability; Applied mathematics; Econometrics; Computation; Bayes estimator; Time series; Statistics; Maximum likelihood; Algorithm","score_opus":0.06111818110951673,"score_gpt":0.4021509902508836,"score_spread":0.34103280914136685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126617033","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00090192474,0.00017230363,0.9984932,0.00007612684,0.000008297917,0.0000053382796,0.00002187288,0.00009422965,0.00022664419],"genre_scores_gemma":[0.17652646,0.0016894137,0.816095,0.00024406928,0.00024552323,0.0003895038,0.0008843204,0.00042861787,0.0034970448],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99530375,0.0036298423,0.00015010173,0.00036127988,0.00047389904,0.00008120905],"domain_scores_gemma":[0.9769081,0.02018165,0.00085674034,0.0012285846,0.0006886249,0.00013627864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069882926,0.00083284575,0.0012981639,0.0014741366,0.000342298,0.0015175735,0.002208702,0.0012894302,0.0027738805],"category_scores_gemma":[0.044858795,0.0006619826,0.00094112987,0.0018862357,0.001645755,0.0027525078,0.0020718528,0.0027209285,0.0010206933],"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":[0.00008385465,0.00007354711,0.0013981968,0.00036585116,0.00019659208,0.00020295139,0.00023469422,0.4469895,0.0021606402,0.44024763,0.0026280724,0.105418585],"study_design_scores_gemma":[0.000012774819,0.000017701203,0.00022879035,0.00002690109,0.000012360896,0.000060854127,0.000018628563,0.85583276,0.00040133588,0.14072022,0.002652261,0.000015464166],"about_ca_topic_score_codex":0.0019403868,"about_ca_topic_score_gemma":0.0015875507,"teacher_disagreement_score":0.0069882926,"about_ca_system_score_codex":0.0006664209,"about_ca_system_score_gemma":0.0012406943,"threshold_uncertainty_score":0.03695804},"labels":[],"label_agreement":null},{"id":"W4282945871","doi":"10.1007/s44199-022-00044-2","title":"Weighted Bayesian Poisson Regression for The Number of Children Ever Born per Woman in Bangladesh","year":2022,"lang":"en","type":"article","venue":"Journal of Statistical Theory and Applications","topic":"Global Maternal and Child Health","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Thompson Rivers University","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Lundbeckfonden; Science and Technology Facilities Council; UNICEF","keywords":"Poisson regression; Poisson distribution; Mathematics; Statistics; Bayesian probability; Regression; Econometrics; Regression analysis; Demography; Sociology","score_opus":0.0075755662174575526,"score_gpt":0.3104459314144035,"score_spread":0.302870365196946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282945871","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15650277,0.0015404643,0.8251271,0.002288777,0.00016318876,0.00034466796,0.0070301527,0.0006221306,0.0063806614],"genre_scores_gemma":[0.83867794,0.002316692,0.13828374,0.0003709518,0.00015766443,0.0009864813,0.0060402225,0.00040631433,0.012759973],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965599,0.0021986596,0.00013894995,0.000672614,0.0002977329,0.0001320674],"domain_scores_gemma":[0.9876237,0.009644076,0.0011628751,0.0006991094,0.00075867027,0.000111566704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010606731,0.0005741491,0.00083209295,0.0011224621,0.00032993278,0.00088288984,0.0021959622,0.0009587877,0.007574255],"category_scores_gemma":[0.04857631,0.000519621,0.0011305619,0.0017055431,0.00064065086,0.0014304285,0.0010073109,0.0015949962,0.0016733627],"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":[0.0004166198,0.00011937695,0.10803912,0.00059053925,0.00058084907,0.0006921344,0.0010750819,0.59183645,0.0020754775,0.16413683,0.011275974,0.1191616],"study_design_scores_gemma":[0.000050678955,0.00009901368,0.032554876,0.00024460335,0.000147198,0.00038828322,0.00031156157,0.88912463,0.00046468424,0.068774134,0.0077141537,0.00012611964],"about_ca_topic_score_codex":0.040209565,"about_ca_topic_score_gemma":0.02543165,"teacher_disagreement_score":0.040209565,"about_ca_system_score_codex":0.0014409471,"about_ca_system_score_gemma":0.0013847334,"threshold_uncertainty_score":0.07995105},"labels":[],"label_agreement":null},{"id":"W4386636102","doi":"10.1007/s44199-023-00062-8","title":"Smoothed Dirichlet Distribution","year":2023,"lang":"en","type":"article","venue":"Journal of Statistical Theory and Applications","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; University of Winnipeg","funders":"","keywords":"Dirichlet distribution; Multinomial distribution; Mathematics; Generalized Dirichlet distribution; Categorical distribution; Concentration parameter; Distribution (mathematics); Marginal distribution; Applied mathematics; Joint probability distribution; Probability distribution; Statistics; Econometrics; Dirichlet's principle; Mathematical analysis; Random variable; Inverse-chi-squared distribution; Distribution fitting","score_opus":0.013350226702433096,"score_gpt":0.30740354703914374,"score_spread":0.29405332033671067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386636102","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014091033,0.0004422213,0.9807719,0.00042996518,0.00016108257,0.00012433509,0.00044979097,0.00049381034,0.0030358387],"genre_scores_gemma":[0.60212916,0.0014063618,0.3717831,0.0007538369,0.0007311219,0.0010349434,0.002505497,0.00040376832,0.019252224],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99485683,0.0022188919,0.0002515707,0.0014650128,0.0008012143,0.00040651413],"domain_scores_gemma":[0.98983735,0.006631006,0.0005619705,0.0016231997,0.0011071351,0.00023924347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0058251265,0.00095129944,0.002018845,0.0025840471,0.0016137633,0.0033232477,0.0034185299,0.0027171928,0.011939281],"category_scores_gemma":[0.023973897,0.001005538,0.0016536304,0.0031332057,0.003191937,0.0051032454,0.001987466,0.0039526955,0.0032538301],"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":[0.00044147728,0.00012790911,0.0058835074,0.00033962927,0.00016555685,0.0005268525,0.0012185163,0.18371257,0.0053586066,0.6512357,0.013047037,0.13794266],"study_design_scores_gemma":[0.000057071764,0.00004151636,0.0014807081,0.000085529544,0.00004633587,0.00034015562,0.00019734773,0.5889646,0.0022804379,0.39566785,0.010765458,0.00007310102],"about_ca_topic_score_codex":0.005471072,"about_ca_topic_score_gemma":0.0051352023,"teacher_disagreement_score":0.011939281,"about_ca_system_score_codex":0.0021376468,"about_ca_system_score_gemma":0.0013344054,"threshold_uncertainty_score":0.039940894},"labels":[],"label_agreement":null},{"id":"W4405189768","doi":"10.1007/s44199-024-00088-6","title":"Assessing the Impact of Geopolitical Risk on Longevity Bond Pricing: Insights from Bayesian Multivariate Regression","year":2024,"lang":"en","type":"article","venue":"Journal of Statistical Theory and Applications","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"University of South Africa; Toronto Metropolitan University","keywords":"Deviance information criterion; Multivariate statistics; Bayesian probability; Akaike information criterion; Posterior probability; Bayesian information criterion; Econometrics; Marginal likelihood; Mathematics; Statistics; Bayesian inference; Computer science","score_opus":0.02132702116760536,"score_gpt":0.39880296240839447,"score_spread":0.3774759412407891,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405189768","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6136914,0.0012385235,0.37905535,0.001478436,0.000036870933,0.000035836805,0.00016846608,0.00020951951,0.0040856316],"genre_scores_gemma":[0.9894079,0.00046247113,0.009150033,0.000046810266,0.000047252328,0.0000101255155,0.00008079193,0.000025758947,0.00076878874],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981548,0.0011239236,0.00007253327,0.00021497805,0.0003102644,0.000123466],"domain_scores_gemma":[0.97839224,0.017128874,0.0023800402,0.00067731045,0.0010918858,0.00032959256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008156916,0.0006097119,0.0010506165,0.0013758981,0.00031794407,0.0016997764,0.00095405965,0.0010872419,0.0016611661],"category_scores_gemma":[0.034572463,0.00041654968,0.00075988594,0.0011557747,0.0008918114,0.0021047324,0.0011892216,0.0014459601,0.0001338192],"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":[0.00014103955,0.00009761273,0.03708516,0.00008083255,0.000208115,0.00028953995,0.00020625256,0.8387032,0.0012658986,0.090540074,0.0008875276,0.030494701],"study_design_scores_gemma":[0.0000032780927,0.000016614762,0.0035407068,0.000008735964,0.000020411475,0.000020732019,0.00002082005,0.98756903,0.000118136,0.008533876,0.00013625668,0.000011368642],"about_ca_topic_score_codex":0.01033953,"about_ca_topic_score_gemma":0.005056135,"teacher_disagreement_score":0.01033953,"about_ca_system_score_codex":0.0007408719,"about_ca_system_score_gemma":0.000772909,"threshold_uncertainty_score":0.043138385},"labels":[],"label_agreement":null},{"id":"W4414219130","doi":"10.1007/s44199-025-00134-x","title":"Modified Linear Failure Rate Distribution for Bathtub Hazard Data","year":2025,"lang":"en","type":"article","venue":"Journal of Statistical Theory and Applications","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; McGill University Health Centre","funders":"","keywords":"Bathtub; Failure rate; Hazard; Maximum likelihood; Distribution (mathematics); Linear regression; Weibull distribution; Linear model","score_opus":0.07009821214888118,"score_gpt":0.40901174484339453,"score_spread":0.33891353269451335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414219130","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058224317,0.0002990681,0.9381018,0.0002697023,0.000047774745,0.00009497646,0.0003955066,0.00043336858,0.0021333988],"genre_scores_gemma":[0.94378537,0.000513675,0.04655948,0.00015249792,0.0000680499,0.0002602715,0.0006750855,0.0001638134,0.00782181],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980557,0.00067375845,0.000096194744,0.00051911856,0.0004301966,0.00022495346],"domain_scores_gemma":[0.99540824,0.0024694207,0.00092598767,0.0005610666,0.0005017291,0.00013347981],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004201111,0.00093422935,0.0011185084,0.0014199052,0.00027984014,0.0011576379,0.0035259777,0.0012498599,0.0034231532],"category_scores_gemma":[0.011710116,0.00036937953,0.0012839491,0.0010159502,0.0013775987,0.0023377924,0.0013250514,0.0016460787,0.0007946736],"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":[0.00044070024,0.00010865964,0.014958195,0.00039769133,0.00014674668,0.0011891471,0.00042496066,0.7556626,0.008372826,0.16511497,0.0026694783,0.050514046],"study_design_scores_gemma":[0.000016813297,0.000105119594,0.0017916823,0.000014279878,0.000026689291,0.00029889634,0.0000362357,0.9656443,0.00090853614,0.029925311,0.0011993706,0.000032640455],"about_ca_topic_score_codex":0.0025053904,"about_ca_topic_score_gemma":0.001301693,"teacher_disagreement_score":0.004201111,"about_ca_system_score_codex":0.0010507691,"about_ca_system_score_gemma":0.00066981534,"threshold_uncertainty_score":0.02221787},"labels":[],"label_agreement":null},{"id":"W4416404588","doi":"10.1007/s44199-025-00132-z","title":"The Modified Instrumental Variable (MIV) for Endogenous Instrumental Variables","year":2025,"lang":"en","type":"article","venue":"Journal of Statistical Theory and Applications","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Instrumental variable; Estimator; Lottery; Earnings; Variable (mathematics); Variables; Quarter (Canadian coin)","score_opus":0.0689276498258833,"score_gpt":0.38176654182534,"score_spread":0.3128388919994567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416404588","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036762652,0.0004138862,0.99386156,0.00033263167,0.00016903362,0.000116647825,0.00012249257,0.00021319611,0.0010942635],"genre_scores_gemma":[0.28376582,0.0009469925,0.70849407,0.000757448,0.0005985933,0.0013308005,0.00044261324,0.00035088568,0.0033127305],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.962648,0.028942265,0.001243695,0.0032132983,0.0031689373,0.0007838376],"domain_scores_gemma":[0.87136453,0.10208287,0.007192301,0.015032262,0.0039228494,0.00040518324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.036230616,0.0013679523,0.002187814,0.0033756143,0.0008965723,0.0027382686,0.005338699,0.0028402398,0.006363007],"category_scores_gemma":[0.19254814,0.0009981984,0.0022404322,0.0033799147,0.0033485705,0.002872748,0.0032504315,0.0055040303,0.0010667259],"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":[0.00024281252,0.00014178845,0.010605383,0.0006880613,0.0011288418,0.0003760901,0.00052218523,0.062746875,0.0016325394,0.79241997,0.0050163665,0.124479085],"study_design_scores_gemma":[0.00027242646,0.00038105447,0.0042572687,0.00077869743,0.00033867278,0.0003630154,0.00020415479,0.47902182,0.0050879032,0.49102873,0.018069359,0.00019687672],"about_ca_topic_score_codex":0.0015595849,"about_ca_topic_score_gemma":0.0008593132,"teacher_disagreement_score":0.036230616,"about_ca_system_score_codex":0.0013278206,"about_ca_system_score_gemma":0.0025265852,"threshold_uncertainty_score":0.19160807},"labels":[],"label_agreement":null}]}