{"meta":{"query_hash":"10ef78be679c","filters":{"venue":"Statistica Neerlandica"},"cohort_total":29,"direct_labels_cover":0,"predictions_cover":29,"exported":29,"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/10ef78be679c","api":"https://metacan.xera.ac/api/v1/cohort?venue=Statistica+Neerlandica"},"results":[{"id":"W1557325407","doi":"10.1111/j.1467-9574.2009.00444.x","title":"Multi-sample simple step-stress experiment under time constraints","year":2009,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Optimal Experimental Design Methods","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":"McMaster University","funders":"","keywords":"Inference; Accelerated life testing; Stress (linguistics); Context (archaeology); Sample (material); Statistical inference; Maximum likelihood; Mathematics; Simple (philosophy); Statistics; Stress testing (software); Sample size determination; Computer science; Econometrics; Artificial intelligence","score_opus":0.10592661547284808,"score_gpt":0.44287912075045915,"score_spread":0.33695250527761106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1557325407","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":[0.11225357,0.00017199626,0.88500655,0.00022621035,0.00006936313,0.0008457903,0.00058048824,0.00021856959,0.0006275117],"genre_scores_gemma":[0.52335656,0.0001516174,0.4692304,0.00031424637,0.000078364785,0.0037246086,0.0009197823,0.000048239515,0.0021761635],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.982982,0.010208788,0.0006821499,0.0038128884,0.0019019208,0.00041230733],"domain_scores_gemma":[0.89225286,0.08791125,0.006239535,0.010298935,0.002496115,0.0008013043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.028042592,0.0010221092,0.0025183668,0.00055240205,0.0005384134,0.00092864403,0.0025391914,0.0022453074,0.004343644],"category_scores_gemma":[0.06319542,0.0010560664,0.0021225682,0.00078600814,0.0019959877,0.0018836233,0.0014526111,0.0023122411,0.00037196832],"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":[0.012987811,0.002165873,0.029230298,0.0020035475,0.0021471865,0.0012626633,0.00083774555,0.52684736,0.04199846,0.21302424,0.0026428762,0.16485187],"study_design_scores_gemma":[0.00081398187,0.0041508777,0.015829422,0.00006458705,0.0003538881,0.00022363568,0.000081690225,0.84757495,0.016639763,0.11139012,0.0027118798,0.00016521374],"about_ca_topic_score_codex":0.0011378499,"about_ca_topic_score_gemma":0.0015731682,"teacher_disagreement_score":0.028042592,"about_ca_system_score_codex":0.0010370708,"about_ca_system_score_gemma":0.0015091039,"threshold_uncertainty_score":0.14830524},"labels":[],"label_agreement":null},{"id":"W1564269117","doi":"10.1111/j.1467-9574.2012.00527.x","title":"Optimum allocation in multivariate stratified random sampling: stochastic matrix mathematical programming","year":2012,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Consejo Nacional de Ciencia y Tecnología; Centre de Recherches Mathématiques","keywords":"Mathematics; Stratified sampling; Multivariate statistics; Covariance matrix; Multivariate normal distribution; Sampling (signal processing); Multivariate t-distribution; Mathematical optimization; Stochastic programming; Matrix (chemical analysis); Sample mean and sample covariance; Covariance; Applied mathematics; Statistics; Computer science","score_opus":0.11444935303429285,"score_gpt":0.4381424851013472,"score_spread":0.3236931320670543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1564269117","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":[0.0023425545,0.00022688464,0.9965837,0.00018166113,0.000021785443,0.000061851126,0.000031939417,0.00003690332,0.00051270204],"genre_scores_gemma":[0.200545,0.0019793708,0.79185414,0.00031314,0.00025465785,0.0014629622,0.00032628953,0.00018126842,0.0030831797],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99021673,0.007934987,0.00017928384,0.00054285914,0.0007482624,0.00037790378],"domain_scores_gemma":[0.9919682,0.006571827,0.0005404257,0.0002595725,0.00044091104,0.00021900448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010264508,0.001629336,0.0029412222,0.0014621887,0.0006148744,0.0017921253,0.0018587293,0.0018261838,0.003038248],"category_scores_gemma":[0.022298148,0.0011458927,0.0020535619,0.0023715533,0.0018732,0.0019451225,0.0019248686,0.0022216728,0.0005045309],"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":[0.00018246842,0.00010135153,0.0007434284,0.00029242414,0.00016479853,0.00009978221,0.00012102112,0.75253457,0.00089231157,0.20756412,0.0019323181,0.035371426],"study_design_scores_gemma":[0.00003237065,0.000067462635,0.00019698884,0.000032812317,0.000030702857,0.00003240806,0.000019893972,0.90557134,0.00033525826,0.0925575,0.0011058776,0.000017386965],"about_ca_topic_score_codex":0.0030537334,"about_ca_topic_score_gemma":0.002609553,"teacher_disagreement_score":0.010264508,"about_ca_system_score_codex":0.0022926398,"about_ca_system_score_gemma":0.003290209,"threshold_uncertainty_score":0.054284513},"labels":[],"label_agreement":null},{"id":"W1572464248","doi":"10.1111/stan.12007","title":"Testing earnings management","year":2013,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":1,"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":"Earnings; Earnings management; Econometrics; Parametric statistics; Sample (material); Quarter (Canadian coin); Series (stratigraphy); Nonparametric statistics; Economics; Mathematics; Statistics; Accounting; Geology; Geography; Physics","score_opus":0.009324789046211087,"score_gpt":0.2037873198197661,"score_spread":0.19446253077355502,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1572464248","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":[0.9900697,0.00014834877,0.0025156934,0.0006092537,0.000039051105,0.00008172441,0.00089868275,0.000057265697,0.005580205],"genre_scores_gemma":[0.9974043,0.000036939906,0.00076536444,0.00005177406,0.000025876774,0.000036774487,0.0005674721,0.0000040748428,0.0011073039],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99625057,0.0014971772,0.0003744037,0.0006221457,0.0007244538,0.00053117593],"domain_scores_gemma":[0.977764,0.010016947,0.007066156,0.0020323105,0.0021093944,0.0010112245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051369513,0.00037934404,0.00032452124,0.001117946,0.00041880706,0.0007778617,0.00084555877,0.0007875211,0.005456813],"category_scores_gemma":[0.027668428,0.00010817162,0.00040935978,0.00079627533,0.00048226857,0.0011562527,0.00071109855,0.00053024484,0.0011536569],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043021288,0.000490077,0.92545843,0.000034371486,0.0001254526,0.00016599683,0.00036202243,0.0010489346,0.001134759,0.0025591936,0.0027487173,0.065441884],"study_design_scores_gemma":[0.00006154841,0.0010580325,0.98234403,0.000022173537,0.000056415996,0.00027646712,0.00075739244,0.0063031614,0.0026512474,0.0023304701,0.0041185534,0.00002054775],"about_ca_topic_score_codex":0.0016857289,"about_ca_topic_score_gemma":0.0014206918,"teacher_disagreement_score":0.005456813,"about_ca_system_score_codex":0.0004378842,"about_ca_system_score_gemma":0.0005905961,"threshold_uncertainty_score":0.027167141},"labels":[],"label_agreement":null},{"id":"W1822370477","doi":"10.1111/stan.12054","title":"Bayesian regression with B‐splines under combinations of shape constraints and smoothness properties","year":2014,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":12,"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":"","keywords":"Smoothness; Mathematics; Multivariate adaptive regression splines; Bayesian probability; Regression; Polygon (computer graphics); Spline (mechanical); Mathematical optimization; Bayesian linear regression; Basis function; B-spline; Applied mathematics; Algorithm; Nonparametric regression; Computer science; Bayesian inference; Statistics; Mathematical analysis","score_opus":0.05104230763589715,"score_gpt":0.323826177699875,"score_spread":0.27278387006397786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1822370477","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":[0.0038883195,0.00021903703,0.99541557,0.00011907269,0.000012413162,0.000012165398,0.000035393965,0.00006724868,0.0002307208],"genre_scores_gemma":[0.25286472,0.002221956,0.7384593,0.0002811955,0.00034567853,0.00044754014,0.00074083207,0.00044330265,0.0041954685],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99239045,0.0048068697,0.00031580293,0.0010700187,0.0011036784,0.00031331365],"domain_scores_gemma":[0.9828012,0.0130888205,0.0015960768,0.0013386713,0.00091774145,0.0002575571],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014073456,0.0015999958,0.0029648072,0.0022493438,0.0008109018,0.0020072353,0.0030039402,0.0025605212,0.0017537101],"category_scores_gemma":[0.034385376,0.0019371813,0.002726157,0.003613444,0.0027689885,0.003482418,0.0029273443,0.004129577,0.00074191723],"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":[0.00018829551,0.000056299283,0.001991908,0.00025039344,0.00018657341,0.00014040429,0.00013439187,0.7600257,0.0028602756,0.16655765,0.0008193221,0.06678881],"study_design_scores_gemma":[0.000028381652,0.000041958287,0.00039296376,0.000026294387,0.000027578022,0.000041976535,0.000012083605,0.9448876,0.00053031114,0.052951027,0.0010347777,0.000025102534],"about_ca_topic_score_codex":0.006781975,"about_ca_topic_score_gemma":0.0041535804,"teacher_disagreement_score":0.014073456,"about_ca_system_score_codex":0.001010488,"about_ca_system_score_gemma":0.0018749385,"threshold_uncertainty_score":0.07442844},"labels":[],"label_agreement":null},{"id":"W1881424619","doi":"10.1111/stan.12028","title":"Adaptive permutation tests for serial independence","year":2014,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bank of Canada; Carleton University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Permutation (music); Independence (probability theory); Random permutation; Random walk; Mathematics; Econometrics; Statistics; Statistical hypothesis testing; Autocorrelation; Algorithm; Combinatorics; Symmetric group","score_opus":0.03181378853635297,"score_gpt":0.24235556111769166,"score_spread":0.2105417725813387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1881424619","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":[0.07334393,0.0003242765,0.9162784,0.0005347387,0.0002607686,0.0005478968,0.0009026578,0.0010809764,0.0067263176],"genre_scores_gemma":[0.7459412,0.00024088965,0.24750695,0.00044006604,0.00036560703,0.0014135664,0.0015662608,0.0002735004,0.002252011],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9735565,0.016453506,0.001629204,0.0037621637,0.003773896,0.00082468626],"domain_scores_gemma":[0.7748412,0.18617964,0.009569662,0.020715201,0.007336677,0.0013576531],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020931153,0.0010730329,0.0013600016,0.0037576908,0.0011749616,0.0023789688,0.0033002477,0.00201879,0.0120389],"category_scores_gemma":[0.18293136,0.0005809424,0.0024818482,0.0042668222,0.0037164665,0.0042791083,0.00247056,0.003435179,0.0012954022],"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":[0.0018535849,0.0005600326,0.070108525,0.0005457224,0.0020208212,0.0017724946,0.00083628966,0.09941041,0.0057096146,0.31616756,0.01016345,0.4908515],"study_design_scores_gemma":[0.000642163,0.0012467896,0.035522554,0.00014179047,0.00032285304,0.0013416676,0.0003196434,0.48299834,0.004763904,0.46554732,0.006833958,0.0003190786],"about_ca_topic_score_codex":0.0010447715,"about_ca_topic_score_gemma":0.0007698928,"teacher_disagreement_score":0.020931153,"about_ca_system_score_codex":0.0010251269,"about_ca_system_score_gemma":0.0027056655,"threshold_uncertainty_score":0.11069584},"labels":[],"label_agreement":null},{"id":"W1921706276","doi":"10.1111/stan.12025","title":"Identifiability of mean‐reverting measurement error with instrumental variable","year":2014,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Income, Poverty, and Inequality","field":"Social Sciences","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":"Université de Sherbrooke","funders":"","keywords":"Observational error; Identifiability; Instrumental variable; Errors-in-variables models; Statistics; Econometrics; Mathematics; Covariance; Context (archaeology); Variance (accounting); Variable (mathematics); Identification (biology); Economics","score_opus":0.03274429186698223,"score_gpt":0.294466150634482,"score_spread":0.26172185876749976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1921706276","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":[0.019959865,0.00032787523,0.97725976,0.0006667272,0.000055584624,0.000040702707,0.00015468369,0.00013827805,0.0013964835],"genre_scores_gemma":[0.7844184,0.0012364038,0.20686463,0.00056806084,0.00033011922,0.0006053661,0.0007630063,0.00021016278,0.005003865],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9760765,0.015454873,0.0010950845,0.0037873758,0.0026779291,0.00090830814],"domain_scores_gemma":[0.86544955,0.104143634,0.01336485,0.013263943,0.0033707046,0.0004073849],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0341449,0.0014392807,0.003250674,0.002030847,0.0010017453,0.0026605723,0.0029367383,0.0025854746,0.002788218],"category_scores_gemma":[0.12373396,0.0011749632,0.0025140247,0.0020643165,0.004540537,0.0045161634,0.0048578624,0.00554167,0.0006788808],"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":[0.00018018227,0.00011559258,0.021442257,0.00043077022,0.00075277407,0.0005468211,0.0010441284,0.097201884,0.0014466147,0.8175336,0.0020538652,0.05725144],"study_design_scores_gemma":[0.00007810578,0.00011405605,0.004908843,0.0001991853,0.00012772404,0.000286898,0.00024583534,0.29132643,0.0029459912,0.69611585,0.0035433574,0.00010776634],"about_ca_topic_score_codex":0.0017895645,"about_ca_topic_score_gemma":0.0009913646,"teacher_disagreement_score":0.0341449,"about_ca_system_score_codex":0.0012833213,"about_ca_system_score_gemma":0.0032585661,"threshold_uncertainty_score":0.18057764},"labels":[],"label_agreement":null},{"id":"W1926189568","doi":"10.1111/j.1467-9574.2012.00524.x","title":"A true simulation study of three estimators at equal protection of respondents in randomized response sampling","year":2012,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Stephen's University","funders":"","keywords":"Estimator; Randomized response; Statistics; Mathematics; Sampling (signal processing); Econometrics; Computer science","score_opus":0.20507386404562242,"score_gpt":0.42678618539677166,"score_spread":0.22171232135114924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1926189568","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":[0.24415095,0.00087278895,0.7490403,0.00074173935,0.00011149815,0.0010553824,0.00012753079,0.00016236813,0.003737467],"genre_scores_gemma":[0.8046076,0.00027939893,0.19255476,0.00026536392,0.000046352925,0.0012017486,0.00013364399,0.00005408993,0.00085699774],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.75635564,0.2308934,0.0018008546,0.003541966,0.0058707,0.0015374783],"domain_scores_gemma":[0.18295848,0.78855455,0.007641652,0.015373807,0.004770102,0.0007013157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.18471882,0.0008986784,0.0015628233,0.0017125999,0.0009158328,0.0021751015,0.0028366498,0.00266346,0.0034195762],"category_scores_gemma":[0.46618316,0.0008898642,0.0021308064,0.0014405876,0.0036964144,0.005932014,0.0023035444,0.002707667,0.00037768635],"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":[0.012502639,0.0021524448,0.042194616,0.0011284496,0.0021292372,0.000315745,0.0035497406,0.51800436,0.0016397266,0.29469723,0.0016699217,0.12001589],"study_design_scores_gemma":[0.0014614034,0.0056154802,0.0072510084,0.00029822552,0.00049010233,0.00047647348,0.0007207174,0.9117938,0.0025329583,0.06715374,0.0020502966,0.00015573717],"about_ca_topic_score_codex":0.0014576772,"about_ca_topic_score_gemma":0.00097611593,"teacher_disagreement_score":0.18471882,"about_ca_system_score_codex":0.002903191,"about_ca_system_score_gemma":0.0016950236,"threshold_uncertainty_score":0.97689813},"labels":[],"label_agreement":null},{"id":"W1975194165","doi":"10.1111/1467-9574.00125","title":"Least squares, preliminary test and Stein‐type estimation in general vector <i>AR</i>(<i>p</i>) models","year":2000,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":12,"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 Regina","funders":"","keywords":"Mathematics; Autoregressive model; Estimator; Statistics; Applied mathematics; Type (biology); Multivariate statistics; Least-squares function approximation; Estimation; Likelihood-ratio test","score_opus":0.03888160437707742,"score_gpt":0.3217836367226706,"score_spread":0.28290203234559314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975194165","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":[0.042248204,0.00050567393,0.9554317,0.00022093471,0.000014813819,0.00002437239,0.00004827018,0.00006912406,0.0014369073],"genre_scores_gemma":[0.6233913,0.0012016518,0.36981317,0.00016436297,0.00012528665,0.00024644315,0.00030008034,0.00007421692,0.0046834648],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99752706,0.0014982272,0.00009903513,0.0002889155,0.000496558,0.00009015455],"domain_scores_gemma":[0.98765135,0.0091366675,0.0011149528,0.0009478766,0.0009629027,0.00018628385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0075250934,0.00070936035,0.00074010954,0.0010503677,0.0002733568,0.00077185786,0.0008292533,0.00076487707,0.0010837776],"category_scores_gemma":[0.037410904,0.00040594977,0.0005716763,0.0009873384,0.0018766187,0.0016626345,0.001449649,0.00082445826,0.00024030147],"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":[0.00027486612,0.00010119322,0.010345545,0.00032743468,0.0002062013,0.00058584946,0.0005404873,0.22066955,0.007323967,0.52670825,0.0024726016,0.23044403],"study_design_scores_gemma":[0.00003406117,0.00031801517,0.006008684,0.000059891518,0.000048274404,0.00032359574,0.00014520415,0.6760231,0.0042518224,0.30972612,0.0029969017,0.00006437008],"about_ca_topic_score_codex":0.0013185813,"about_ca_topic_score_gemma":0.0014340183,"teacher_disagreement_score":0.0075250934,"about_ca_system_score_codex":0.00046104274,"about_ca_system_score_gemma":0.0012058876,"threshold_uncertainty_score":0.03979695},"labels":[],"label_agreement":null},{"id":"W1977315000","doi":"10.1111/j.1467-9574.2009.00417.x","title":"Estimation and model adequacy checking for multivariate seasonal autoregressive time series models with periodically varying parameters","year":2009,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Autocovariance; Autoregressive model; Mathematics; Autocorrelation; Estimator; Series (stratigraphy); Statistics; Multivariate statistics; Autoregressive integrated moving average; Time series; Asymptotic distribution; Bivariate analysis; Applied mathematics","score_opus":0.027815927645592226,"score_gpt":0.24261796643068115,"score_spread":0.2148020387850889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977315000","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":[0.1485512,0.0002315221,0.84941065,0.00023935008,0.000018194774,0.00006654077,0.00021405375,0.0002863782,0.0009820266],"genre_scores_gemma":[0.89486426,0.00029821804,0.10304117,0.000060625105,0.000059122936,0.00020872253,0.0008067483,0.00007287429,0.00058822974],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9946748,0.0035575838,0.00026841566,0.00059966475,0.0006988989,0.00020059646],"domain_scores_gemma":[0.94703877,0.04602064,0.002620493,0.002544655,0.001571954,0.00020339027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013316606,0.0007725702,0.0011124134,0.0016670807,0.0004352904,0.0011599173,0.0011548112,0.00084656774,0.00150818],"category_scores_gemma":[0.06928689,0.0005576119,0.0014807512,0.0009808925,0.0009745484,0.0018777559,0.0013933218,0.0016053697,0.00017293295],"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":[0.00020564233,0.00015736438,0.036314547,0.00016798386,0.00039310887,0.00039904402,0.00036413153,0.82218945,0.0027349507,0.06213855,0.0008520618,0.0740832],"study_design_scores_gemma":[0.0000138425785,0.000063933316,0.003567671,0.000016762817,0.000024726321,0.000060944476,0.00004637238,0.9745136,0.00054730737,0.020779813,0.00034539847,0.000019703488],"about_ca_topic_score_codex":0.006314711,"about_ca_topic_score_gemma":0.0043855417,"teacher_disagreement_score":0.013316606,"about_ca_system_score_codex":0.00055363757,"about_ca_system_score_gemma":0.001962512,"threshold_uncertainty_score":0.07042575},"labels":[],"label_agreement":null},{"id":"W2014262831","doi":"10.1111/1467-9574.t01-1-00057","title":"A new approximation of the posterior distribution of the log–odds ratio","year":2002,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","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":"Université de Montréal; University of Waterloo","funders":"","keywords":"Dirichlet distribution; Mathematics; Multinomial distribution; Distribution (mathematics); Posterior probability; Concentration parameter; Applied mathematics; Statistics; Mathematical analysis; Bayesian probability","score_opus":0.014094731546854549,"score_gpt":0.23518343713262224,"score_spread":0.22108870558576768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014262831","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":[0.002600365,0.00054295897,0.9954725,0.00020450304,0.00006649735,0.000014869041,0.000051099243,0.00011604469,0.00093112217],"genre_scores_gemma":[0.2189376,0.0048127477,0.76522094,0.00061962527,0.0009098491,0.00032400034,0.00078796694,0.00046239447,0.007924958],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99737954,0.0011006302,0.00011023244,0.0005121704,0.0007500633,0.00014730866],"domain_scores_gemma":[0.9879219,0.009999108,0.00054977083,0.00060502277,0.0007457207,0.00017848598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055819997,0.0010690067,0.0013917973,0.0027204019,0.00057606405,0.0025311294,0.003174286,0.0018159973,0.00554807],"category_scores_gemma":[0.042535827,0.0008363879,0.0012169866,0.0021010123,0.0022171796,0.005271118,0.0017146905,0.0033425877,0.0016258012],"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":[0.00031781438,0.00008980573,0.0049540102,0.00051884144,0.00018643137,0.00057648367,0.0005735104,0.28639197,0.004013158,0.5116343,0.007152321,0.1835914],"study_design_scores_gemma":[0.000040109033,0.00004080104,0.0010938051,0.00011675517,0.00005525321,0.0006752816,0.000065158856,0.8424042,0.0012590183,0.14579394,0.008396982,0.00005867695],"about_ca_topic_score_codex":0.003108809,"about_ca_topic_score_gemma":0.0018522139,"teacher_disagreement_score":0.0055819997,"about_ca_system_score_codex":0.0012112568,"about_ca_system_score_gemma":0.0011049864,"threshold_uncertainty_score":0.02952081},"labels":[],"label_agreement":null},{"id":"W2021688446","doi":"10.1046/j.0039-0402.2003.00254.x","title":"Regressor and random‐effects dependencies in multilevel models","year":2004,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":81,"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","funders":"","keywords":"Independence (probability theory); Econometrics; Monte Carlo method; Random effects model; Computer science; Multilevel model; Statistics; Machine learning; Mathematics; Meta-analysis","score_opus":0.10038898709520844,"score_gpt":0.38229869015186063,"score_spread":0.2819097030566522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021688446","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":[0.0128924,0.0015819089,0.98194075,0.0010608609,0.00007148097,0.00013614054,0.00028647605,0.00019144885,0.0018386417],"genre_scores_gemma":[0.34227362,0.0032747681,0.6483158,0.0005885996,0.0003271921,0.0014466306,0.00083354453,0.00023409659,0.0027058222],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9215731,0.06756457,0.001760258,0.003760204,0.00431325,0.0010286828],"domain_scores_gemma":[0.752109,0.22569986,0.008245251,0.010782436,0.0025065788,0.0006568292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0545257,0.0013480695,0.0026057754,0.0029248316,0.0014206311,0.0029470075,0.0038956737,0.0027906972,0.0066278577],"category_scores_gemma":[0.20773533,0.0016318044,0.003961497,0.00431221,0.0034419126,0.0054394454,0.0035396516,0.00546073,0.00091576943],"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":[0.00021135423,0.0001388324,0.013158617,0.0008190303,0.0014728156,0.00036613343,0.0011100699,0.088475145,0.00034392523,0.8185272,0.0022914503,0.07308548],"study_design_scores_gemma":[0.000106283274,0.00018961087,0.006081402,0.00040790756,0.00068814086,0.00020513344,0.00019634506,0.25370693,0.0006005461,0.7311198,0.0065943254,0.00010345899],"about_ca_topic_score_codex":0.0070658554,"about_ca_topic_score_gemma":0.008350268,"teacher_disagreement_score":0.0545257,"about_ca_system_score_codex":0.0018658087,"about_ca_system_score_gemma":0.0035232843,"threshold_uncertainty_score":0.28836292},"labels":[],"label_agreement":null},{"id":"W2075933254","doi":"10.1111/j.1467-9574.2005.00297.x","title":"Studentization and prediction in a multivariate normal setting","year":2005,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Bayesian Modeling and Causal Inference","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 Toronto","funders":"","keywords":"Mathematics; Multivariate normal distribution; Multivariate statistics; Bayes' theorem; Posterior predictive distribution; Statistic; Prior probability; Statistics; Applied mathematics; Bayesian probability; Bayesian linear regression; Bayesian inference","score_opus":0.008632794826039257,"score_gpt":0.2562568950295276,"score_spread":0.24762410020348832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075933254","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":[0.028331973,0.0002563094,0.9643842,0.0010355979,0.000047226054,0.000034832203,0.00008048161,0.00019583562,0.0056335344],"genre_scores_gemma":[0.87693137,0.0008532172,0.11253174,0.0004231257,0.00037025538,0.00022695313,0.00029933226,0.00017409498,0.008189804],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99449855,0.0030686304,0.00014986261,0.0009793612,0.00084687205,0.000456753],"domain_scores_gemma":[0.97646546,0.017038014,0.0021485495,0.0022177347,0.0015872224,0.00054307235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012194908,0.00080499635,0.0012745933,0.0017280821,0.00095954293,0.002280605,0.0020347966,0.0017804591,0.007615294],"category_scores_gemma":[0.05065308,0.00053907663,0.0010367034,0.0016475071,0.006949012,0.005794428,0.002361427,0.0028696738,0.0009343459],"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":[0.000031303734,0.000016724425,0.0011626496,0.000021837572,0.000015917396,0.000049516126,0.00011165529,0.019562986,0.00013442432,0.96596634,0.00067638746,0.012250305],"study_design_scores_gemma":[0.000014116548,0.000017900009,0.0005426559,0.000017504795,0.0000062681424,0.000034731092,0.000026466383,0.15628967,0.00020732192,0.8419926,0.0008360529,0.000014773855],"about_ca_topic_score_codex":0.003528265,"about_ca_topic_score_gemma":0.0026296533,"teacher_disagreement_score":0.012194908,"about_ca_system_score_codex":0.0019718045,"about_ca_system_score_gemma":0.0016647498,"threshold_uncertainty_score":0.0644936},"labels":[],"label_agreement":null},{"id":"W2081288091","doi":"10.1111/1467-9574.00147","title":"On the generalized Poisson distribution","year":2000,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Poisson distribution; Mathematics; Compound Poisson distribution; Zero-inflated model; Lemma (botany); Distribution (mathematics); Combinatorics; Euler's formula; Infinite divisibility; Pure mathematics; Statistics; Mathematical analysis; Poisson regression","score_opus":0.04356478477285422,"score_gpt":0.3335353835731968,"score_spread":0.2899705988003426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081288091","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":[0.041100606,0.0020929493,0.92088556,0.002278434,0.00039975237,0.00005637226,0.00035904793,0.00016924563,0.03265804],"genre_scores_gemma":[0.74256176,0.010199353,0.19278671,0.002908802,0.0025992861,0.0006446115,0.0014178857,0.00049328886,0.046388213],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978908,0.00080126117,0.00007780834,0.00037552207,0.00061678776,0.00023788222],"domain_scores_gemma":[0.9960078,0.0021930945,0.00043004288,0.00040090483,0.0007490459,0.00021904113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041234144,0.00070430763,0.00096872833,0.00268585,0.0008705404,0.001914141,0.0015165232,0.00088962814,0.0066056484],"category_scores_gemma":[0.013798998,0.00042672173,0.0011135914,0.0022904507,0.0029387875,0.0039109206,0.0024474708,0.0024047513,0.0013997508],"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":[0.0000063247467,0.0000027541664,0.00027479487,0.00001362632,0.0000076117385,0.00005121367,0.000059698432,0.0029234106,0.00019199659,0.99146044,0.00085157034,0.0041567422],"study_design_scores_gemma":[0.000010531726,0.000008292494,0.0003845067,0.00002344872,0.0000066880866,0.00017490248,0.000037607708,0.03412658,0.00025404806,0.9583886,0.0065686028,0.000016094182],"about_ca_topic_score_codex":0.0030444956,"about_ca_topic_score_gemma":0.0009814351,"teacher_disagreement_score":0.0066056484,"about_ca_system_score_codex":0.001538503,"about_ca_system_score_gemma":0.0010597743,"threshold_uncertainty_score":0.022098124},"labels":[],"label_agreement":null},{"id":"W2081405537","doi":"10.1111/j.1467-9574.2005.00292.x","title":"Processes with volatility‐induced stationarity: an application for interest rates","year":2005,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nickel Institute","funders":"","keywords":"Volatility (finance); Econometrics; Forward volatility; Logarithm; Stochastic volatility; Volatility smile; Implied volatility; Volatility swap; Martingale (probability theory); Economics; Mathematics; Statistics","score_opus":0.04566042821931492,"score_gpt":0.2805313445191252,"score_spread":0.23487091629981027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081405537","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":[0.02264905,0.0005100869,0.97265786,0.000546123,0.000120137775,0.0000297689,0.000037476984,0.000073210016,0.0033763435],"genre_scores_gemma":[0.71246916,0.0028969685,0.27650374,0.00052780967,0.0014380793,0.00022464988,0.0001788706,0.00015336719,0.00560739],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990013,0.00041534044,0.00007915225,0.00018327768,0.00025380292,0.000067155524],"domain_scores_gemma":[0.99387395,0.0044345944,0.0006660273,0.00045327033,0.00040567663,0.0001665794],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030586424,0.00069341576,0.0009859994,0.0013559213,0.000578399,0.0011652119,0.0009420706,0.0014284933,0.0021862702],"category_scores_gemma":[0.011071252,0.0003579002,0.0021036342,0.0013068477,0.0019959707,0.0018505633,0.0016634855,0.0028492578,0.00031412995],"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":[0.000023171868,0.000038381757,0.0010431797,0.0000657805,0.000044200737,0.000303602,0.0002041435,0.045698162,0.002723897,0.9328473,0.0004385766,0.016569674],"study_design_scores_gemma":[0.000030714767,0.00009197755,0.000846281,0.00004366057,0.000041000603,0.00032036263,0.000064082764,0.4899184,0.0019148856,0.50203395,0.004654078,0.0000406003],"about_ca_topic_score_codex":0.0011192828,"about_ca_topic_score_gemma":0.0006286734,"teacher_disagreement_score":0.0030586424,"about_ca_system_score_codex":0.00074153667,"about_ca_system_score_gemma":0.0009289782,"threshold_uncertainty_score":0.016175866},"labels":[],"label_agreement":null},{"id":"W2103818588","doi":"10.1111/j.1467-9574.2011.00491.x","title":"Estimation strategies for the regression coefficient parameter matrix in multivariate multiple regression","year":2011,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":19,"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 Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Estimator; Mathematics; Subspace topology; Context (archaeology); Linear regression; Multivariate statistics; Statistics; Monte Carlo method; Regression analysis; Applied mathematics; Mathematical optimization","score_opus":0.15532506896838816,"score_gpt":0.44047722026870595,"score_spread":0.2851521513003178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103818588","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":[0.0019382524,0.0001848944,0.99766374,0.000054092838,0.0000048650973,0.0000150647365,0.000011038532,0.000030338846,0.0000977192],"genre_scores_gemma":[0.11177242,0.0014524462,0.8845704,0.00013092415,0.00011015565,0.000336062,0.0001799711,0.000121013,0.0013265156],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99413496,0.004304339,0.00020877532,0.0005795887,0.00065814785,0.000114063696],"domain_scores_gemma":[0.9841001,0.012785361,0.001050714,0.0008260594,0.0011173631,0.00012038026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013264186,0.0011475917,0.0014736489,0.0014392711,0.0003512214,0.0010172141,0.0024532042,0.0013705447,0.0018973968],"category_scores_gemma":[0.04009044,0.0007077108,0.0010121699,0.0019516076,0.0010550839,0.0026674415,0.0016555146,0.0018757881,0.00068224216],"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":[0.000119975666,0.00009360232,0.0024084018,0.00050482625,0.00023738242,0.00019439292,0.0002860401,0.5713573,0.0055099064,0.18911466,0.0014806238,0.2286929],"study_design_scores_gemma":[0.000022804821,0.00007001687,0.0004897376,0.00005063926,0.00004162665,0.000056457386,0.000017753115,0.9553613,0.0013036693,0.04133258,0.001223229,0.000030255538],"about_ca_topic_score_codex":0.0014845642,"about_ca_topic_score_gemma":0.0016912759,"teacher_disagreement_score":0.013264186,"about_ca_system_score_codex":0.00054729223,"about_ca_system_score_gemma":0.00090901484,"threshold_uncertainty_score":0.07014853},"labels":[],"label_agreement":null},{"id":"W2124322287","doi":"10.1111/j.1467-9574.2011.00490.x","title":"Bayesian clustering with priors on partitions","year":2011,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Data Mining Algorithms and Applications","field":"Computer Science","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":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cluster analysis; Prior probability; Bayesian probability; Partition (number theory); Posterior probability; Computer science; Stylometry; Data mining; Mathematics; Artificial intelligence; Algorithm; Machine learning","score_opus":0.025334773401883143,"score_gpt":0.23339167957134108,"score_spread":0.20805690616945793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124322287","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":[0.0064657703,0.00035407644,0.98989534,0.0004106133,0.000042038297,0.000094022726,0.00032461496,0.00021373988,0.0021997208],"genre_scores_gemma":[0.20053135,0.0010628577,0.79064447,0.00049321604,0.00035786763,0.00078215776,0.002371864,0.00031249036,0.0034436793],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98120373,0.009741288,0.0010305652,0.0047631296,0.0026606575,0.00060055126],"domain_scores_gemma":[0.9630858,0.024257576,0.0022543524,0.006661537,0.0031947717,0.00054601114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.018586334,0.0016134061,0.0028569794,0.005543778,0.0029400773,0.0075551528,0.0049472977,0.0038794354,0.004192719],"category_scores_gemma":[0.07882878,0.0022276868,0.0027834387,0.005766856,0.0055964096,0.008987025,0.005925418,0.0056516137,0.0021797067],"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":[0.00029174495,0.000080379425,0.0041626436,0.00035252224,0.00030655102,0.00013214743,0.001221507,0.28352967,0.0009766013,0.60829383,0.0068740672,0.09377839],"study_design_scores_gemma":[0.000041402098,0.000024832838,0.0008845239,0.00011852271,0.00004269426,0.000065800254,0.000121743,0.30820423,0.0005449336,0.6853018,0.0045945775,0.000054974233],"about_ca_topic_score_codex":0.0043213507,"about_ca_topic_score_gemma":0.005977709,"teacher_disagreement_score":0.018586334,"about_ca_system_score_codex":0.0036179414,"about_ca_system_score_gemma":0.0030179538,"threshold_uncertainty_score":0.09829515},"labels":[],"label_agreement":null},{"id":"W2144350677","doi":"10.1111/j.1467-9574.2005.00287.x","title":"Neyman type A distribution revisited","year":2005,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Unimodality; Type (biology); Distribution (mathematics); Combinatorics; Statistics; Mathematical analysis","score_opus":0.050269039736118994,"score_gpt":0.3694813309249098,"score_spread":0.3192122911887908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144350677","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":[0.012621888,0.008856731,0.9140507,0.0078529995,0.0011121909,0.00006195986,0.00018083845,0.00017817835,0.055084415],"genre_scores_gemma":[0.7389886,0.01430353,0.18306717,0.005892803,0.005048314,0.00029749895,0.00020049242,0.00029787142,0.051903743],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9918045,0.0037185391,0.0004112326,0.0012836523,0.0023340145,0.0004481175],"domain_scores_gemma":[0.96520644,0.025390862,0.00227799,0.0024604534,0.004071073,0.0005931305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014625514,0.00072645955,0.0014442008,0.0023502011,0.0014874416,0.0044726944,0.0020802508,0.003377394,0.008519798],"category_scores_gemma":[0.052051496,0.00065252604,0.0012204585,0.0029117854,0.005179332,0.006648452,0.0021949501,0.005458239,0.0019986227],"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":[0.00001667036,0.0000069622356,0.00035049175,0.00004524241,0.000019085195,0.00016461217,0.00009509911,0.0017013712,0.0001956293,0.9821301,0.0024197516,0.012855023],"study_design_scores_gemma":[0.0000138189735,0.000028409584,0.0003713057,0.0000781688,0.000016920028,0.0006152465,0.000089063746,0.017915959,0.00028172496,0.96875495,0.011810648,0.000023775792],"about_ca_topic_score_codex":0.0022386697,"about_ca_topic_score_gemma":0.0012287573,"teacher_disagreement_score":0.014625514,"about_ca_system_score_codex":0.0025080447,"about_ca_system_score_gemma":0.0032264062,"threshold_uncertainty_score":0.07734805},"labels":[],"label_agreement":null},{"id":"W2153537366","doi":"10.1111/1467-9574.00209","title":"A Bayesian adaptive design in clinical trials for continuous responses","year":2002,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":10,"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 de Montréal","funders":"","keywords":"Bayesian probability; Computer science; Clinical trial; Convergence (economics); Covariate; Adaptive design; Bayesian inference; Mathematical optimization; Econometrics; Artificial intelligence; Machine learning; Mathematics; Medicine; Economics","score_opus":0.8210327105601135,"score_gpt":0.6167936388702271,"score_spread":0.20423907168988642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153537366","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016301653,0.00043373636,0.9956344,0.0005508315,0.00015302649,0.0009193545,0.000050606446,0.00011773625,0.00051021506],"genre_scores_gemma":[0.06325255,0.00074067,0.9233569,0.0007789616,0.00028590797,0.010290901,0.00011637787,0.00004086943,0.0011368796],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.74645054,0.2366307,0.0036091406,0.0067534326,0.0056001167,0.0009560772],"domain_scores_gemma":[0.83928984,0.13965224,0.007579098,0.008331928,0.0041125803,0.0010343222],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.15878922,0.0028705073,0.004046332,0.002312601,0.00089049054,0.0028630975,0.0033634417,0.006499538,0.006912815],"category_scores_gemma":[0.20418751,0.0017703908,0.0026393938,0.0028076128,0.005638964,0.003735388,0.0030843283,0.006632166,0.0016651675],"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":[0.0031714542,0.00031961408,0.0018648686,0.0015730808,0.00093989755,0.00025661002,0.0006563282,0.10512801,0.0019826996,0.7444558,0.0040666955,0.13558494],"study_design_scores_gemma":[0.004108387,0.0034813103,0.0010440893,0.00056590105,0.00044364698,0.00023545706,0.000061631385,0.3949337,0.0014093103,0.5803914,0.013128017,0.00019700876],"about_ca_topic_score_codex":0.0005790813,"about_ca_topic_score_gemma":0.0005970038,"teacher_disagreement_score":0.8412108,"about_ca_system_score_codex":0.0020545863,"about_ca_system_score_gemma":0.0035626781,"threshold_uncertainty_score":0.8397677},"labels":[],"label_agreement":null},{"id":"W2156619449","doi":"10.1111/j.1467-9574.2012.00522.x","title":"Hierarchical clustering of spatially correlated functional data","year":2012,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":80,"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":"Cluster analysis; Functional data analysis; Variogram; Geostatistics; Mathematics; Spatial analysis; Data mining; Context (archaeology); Hierarchical clustering; Data set; Computer science; TRACE (psycholinguistics); Basis (linear algebra); Set (abstract data type); Statistics; Kriging; Spatial variability; Geography","score_opus":0.03146352202865006,"score_gpt":0.25603179237855844,"score_spread":0.2245682703499084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156619449","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":[0.12540585,0.0005802441,0.8709089,0.00020508414,0.000027544695,0.00015105192,0.00062877353,0.00051009055,0.0015824876],"genre_scores_gemma":[0.7619075,0.00030345956,0.23380932,0.000081891005,0.00004922759,0.00028066052,0.0022171976,0.00013757312,0.0012131273],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9944528,0.0028277345,0.00028462606,0.0010880715,0.0009908557,0.0003560054],"domain_scores_gemma":[0.99105144,0.0042132935,0.0012764335,0.0018117054,0.0014427083,0.00020446946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005185576,0.00072213303,0.0012005755,0.007389365,0.0010942197,0.0017062536,0.001320264,0.00080650504,0.0011355166],"category_scores_gemma":[0.0191323,0.00045939477,0.0014638193,0.0052862135,0.0011992799,0.0010898578,0.0014896202,0.00086721714,0.00042353134],"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":[0.00031892722,0.00018039557,0.0531831,0.0005959828,0.0010683311,0.0005106915,0.0020774892,0.59233975,0.008611043,0.083724216,0.0048081386,0.2525819],"study_design_scores_gemma":[0.000024285275,0.000049522023,0.023150168,0.000061818464,0.000089807596,0.00010741194,0.00036285582,0.8638979,0.0011199468,0.10836843,0.0027060076,0.00006190979],"about_ca_topic_score_codex":0.011854394,"about_ca_topic_score_gemma":0.011840739,"teacher_disagreement_score":0.011854394,"about_ca_system_score_codex":0.0019451671,"about_ca_system_score_gemma":0.0013686364,"threshold_uncertainty_score":0.027424276},"labels":[],"label_agreement":null},{"id":"W2169811924","doi":"10.1111/stan.12014","title":"Comment on ‘Type I error and test power of different tests for testing interaction effects in factorial experiments’","year":2013,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Advanced Statistical Methods and Models","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":"York University","funders":"Deutsche Forschungsgemeinschaft","keywords":"Type I and type II errors; Factorial; Factorial experiment; Rank (graph theory); Mathematics; Transformation (genetics); Statistics; Fractional factorial design; Type (biology); Test (biology); Power (physics); Combinatorics","score_opus":0.12409628172774459,"score_gpt":0.4345074746872428,"score_spread":0.31041119295949826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169811924","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00038572086,0.0017508747,0.00289923,0.9301235,0.06261679,0.000063470834,0.0004324937,0.00047479034,0.0012531561],"genre_scores_gemma":[0.002232383,0.00039693087,0.0018674168,0.9710028,0.022792134,0.00012040575,0.000043978474,0.00013119935,0.0014128012],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9568823,0.012282971,0.009492496,0.0063766413,0.013125554,0.0018399507],"domain_scores_gemma":[0.72518396,0.19861844,0.014219937,0.010122581,0.047240507,0.004614607],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.049682304,0.0026140446,0.003221671,0.0027242843,0.003656996,0.004119543,0.008777457,0.058536753,0.009568437],"category_scores_gemma":[0.29321373,0.0020535197,0.0045536486,0.0030777962,0.016698197,0.007934889,0.003787589,0.063446,0.014513363],"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":[0.000081024344,0.000022482747,0.00045441222,0.0002109141,0.00004837728,0.000316596,0.00032504887,0.00013480402,0.00032728133,0.0037082245,0.98968834,0.00468251],"study_design_scores_gemma":[0.0002826465,0.00021756244,0.0046106754,0.0011157905,0.00017285795,0.0022376173,0.00068043533,0.0013270611,0.0021733548,0.03840034,0.9484193,0.0003623692],"about_ca_topic_score_codex":0.012607794,"about_ca_topic_score_gemma":0.0094137415,"teacher_disagreement_score":0.9503177,"about_ca_system_score_codex":0.005319386,"about_ca_system_score_gemma":0.00502859,"threshold_uncertainty_score":0.2627483},"labels":[],"label_agreement":null},{"id":"W2475637399","doi":"10.1111/stan.12092","title":"A Skew‐normal copula‐driven GLMM","year":2016,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Statistical Distribution Estimation and Applications","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":"Collège de Maisonneuve; McGill University","funders":"","keywords":"Copula (linguistics); Skew; Bivariate analysis; Mathematics; Monte Carlo method; Econometrics; Statistics; Computer science","score_opus":0.04996951293043424,"score_gpt":0.35370198993181073,"score_spread":0.3037324770013765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2475637399","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":[0.009564953,0.0002876976,0.9824144,0.0004543179,0.00023621952,0.00032649163,0.0035220145,0.001983168,0.0012106061],"genre_scores_gemma":[0.11993857,0.0005484835,0.8587803,0.00063755404,0.00018755802,0.00228903,0.007845751,0.0015902714,0.00818248],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9951656,0.0029861482,0.00019087442,0.0010578111,0.00039157362,0.00020792698],"domain_scores_gemma":[0.9947082,0.0034194395,0.00030604177,0.00073033833,0.0007122158,0.00012377593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009085063,0.0018937511,0.0017114092,0.0017441607,0.0009069554,0.0023367885,0.0037665516,0.0020577142,0.014813015],"category_scores_gemma":[0.023460736,0.0015845862,0.0035152228,0.0029773884,0.0008687,0.002512338,0.0029989206,0.0038485515,0.00620549],"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":[0.0006407481,0.0003354142,0.012788438,0.0007232141,0.0018341824,0.00055272167,0.000924467,0.40266037,0.0043139295,0.120637685,0.043718673,0.41087016],"study_design_scores_gemma":[0.0000917165,0.00019500745,0.003785827,0.0001539504,0.00019737972,0.000195176,0.00014515805,0.888719,0.0012614299,0.08393014,0.021181688,0.00014351876],"about_ca_topic_score_codex":0.008106243,"about_ca_topic_score_gemma":0.013261797,"teacher_disagreement_score":0.014813015,"about_ca_system_score_codex":0.0012271082,"about_ca_system_score_gemma":0.0034596026,"threshold_uncertainty_score":0.049554467},"labels":[],"label_agreement":null},{"id":"W2533485301","doi":"10.1111/stan.12098","title":"Penalty and related estimation strategies in the spatial error model","year":2016,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University; University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Estimator; Autoregressive model; Spatial analysis; Computer science; Spatial dependence; Regression analysis; Econometrics; Spatial econometrics; Regression; Mathematics; Statistics","score_opus":0.028955729958036473,"score_gpt":0.2455300021074678,"score_spread":0.21657427214943134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2533485301","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":[0.002685291,0.00017245476,0.9964455,0.00020806876,0.000022934944,0.000012930455,0.00002419649,0.000040680985,0.0003878856],"genre_scores_gemma":[0.21443711,0.0013977585,0.774014,0.0004342903,0.00033762684,0.00047831677,0.0005023431,0.00028417044,0.008114443],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9942417,0.0041326405,0.00022613764,0.00047904346,0.0007530053,0.00016747334],"domain_scores_gemma":[0.9641057,0.030259525,0.001456633,0.0022519662,0.0016176177,0.00030853375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012658511,0.000909289,0.0012804882,0.0014087048,0.00051825185,0.0011920932,0.0028949277,0.0015718207,0.002991745],"category_scores_gemma":[0.058154617,0.00062868785,0.0009263676,0.0016683907,0.002094239,0.0033408678,0.002728621,0.0030340278,0.0007091414],"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":[0.0001102849,0.00008263928,0.0022021732,0.00021192012,0.000110631685,0.00017528271,0.00019137621,0.3076678,0.0010315656,0.57250214,0.002440989,0.11327317],"study_design_scores_gemma":[0.000016587004,0.00003438435,0.00040001317,0.000031495223,0.00001422227,0.00006183708,0.000021011778,0.8377417,0.0004023361,0.15938118,0.0018746203,0.000020646248],"about_ca_topic_score_codex":0.0018072072,"about_ca_topic_score_gemma":0.001591266,"teacher_disagreement_score":0.012658511,"about_ca_system_score_codex":0.00066054345,"about_ca_system_score_gemma":0.0012109978,"threshold_uncertainty_score":0.066945374},"labels":[],"label_agreement":null},{"id":"W3035440905","doi":"10.1111/stan.12220","title":"Shrinkage estimation of the exponentiated Weibull regression model for time‐to‐event data","year":2020,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","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":"University of Saskatchewan; University of Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Estimator; Weibull distribution; Statistical inference; Mathematics; Shrinkage; Statistics; Inference; Event (particle physics); Regression analysis; Regression; Econometrics; Applied mathematics; Computer science; Artificial intelligence","score_opus":0.10996638888019235,"score_gpt":0.3793251674136895,"score_spread":0.26935877853349716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035440905","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":[0.012165332,0.00022353372,0.9866803,0.00012545935,0.000028686165,0.000034870816,0.0000811878,0.000122011275,0.00053862896],"genre_scores_gemma":[0.5741646,0.0023755012,0.4145165,0.0002727341,0.00030722056,0.00059810205,0.001531171,0.00029039636,0.00594377],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99730057,0.0015793962,0.00014033561,0.00034676222,0.00051962916,0.000113402566],"domain_scores_gemma":[0.98863864,0.0073294207,0.001108889,0.0016954646,0.0011022992,0.00012531024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009533501,0.000748683,0.0010345855,0.001264534,0.00027389528,0.00073350506,0.0015184451,0.0008848858,0.0017532838],"category_scores_gemma":[0.03287895,0.00035179913,0.0011511742,0.0013892369,0.0008840629,0.0017073886,0.0013800616,0.0017491116,0.0007451164],"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":[0.00033459943,0.00012375641,0.01715273,0.00052857475,0.0003084936,0.00042025125,0.0005606354,0.4271568,0.011861352,0.18336345,0.005228311,0.35296094],"study_design_scores_gemma":[0.000023573202,0.00009421739,0.0039549884,0.00005238779,0.000042373897,0.0002216155,0.00005259263,0.92226934,0.0023298378,0.066549145,0.004367948,0.000041960382],"about_ca_topic_score_codex":0.0010202067,"about_ca_topic_score_gemma":0.0009092366,"teacher_disagreement_score":0.009533501,"about_ca_system_score_codex":0.00039123383,"about_ca_system_score_gemma":0.0008928376,"threshold_uncertainty_score":0.050418556},"labels":[],"label_agreement":null},{"id":"W3168316256","doi":"10.1111/stan.12250","title":"Information anchored reference‐based sensitivity analysis for truncated normal data with application to survival analysis","year":2021,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; Medical Research Council Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; London School of Hygiene and Tropical Medicine","keywords":"Censoring (clinical trials); Covariate; Inference; Imputation (statistics); Econometrics; Statistics; Computer science; Tobit model; Conditional probability distribution; Mathematics; Missing data; Robustness (evolution); Statistical inference; Data mining; Artificial intelligence","score_opus":0.06785236872376028,"score_gpt":0.3731215192547555,"score_spread":0.30526915053099524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3168316256","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":[0.0024512953,0.00089865667,0.9941273,0.0005839704,0.000074281,0.00029644754,0.000121110796,0.00013206758,0.0013148917],"genre_scores_gemma":[0.25428224,0.00238267,0.7350048,0.0012218844,0.00028466858,0.0033794176,0.00042990668,0.00038926804,0.002625111],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.85647255,0.13201366,0.0025024184,0.0030954392,0.0050729695,0.0008428572],"domain_scores_gemma":[0.51551926,0.45699966,0.009047811,0.0120424945,0.0055588717,0.0008319176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.18208206,0.0021770296,0.0038799183,0.004961506,0.0011228267,0.0036707562,0.0039946907,0.003295129,0.009276884],"category_scores_gemma":[0.40959203,0.0015909116,0.0061411033,0.0033974422,0.0040915078,0.0046935515,0.006233595,0.008449301,0.00067436305],"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":[0.0007273956,0.00019077293,0.0025898619,0.0017595564,0.0014566954,0.0010913057,0.0011152478,0.3039723,0.0011194932,0.62051743,0.0030519713,0.062408056],"study_design_scores_gemma":[0.00015930642,0.0002351331,0.0005426888,0.00039217077,0.00028106503,0.00026604207,0.00008594887,0.4748475,0.00069598475,0.51813525,0.0042779595,0.00008101377],"about_ca_topic_score_codex":0.0027768894,"about_ca_topic_score_gemma":0.001575422,"teacher_disagreement_score":0.18208206,"about_ca_system_score_codex":0.00358846,"about_ca_system_score_gemma":0.0037572177,"threshold_uncertainty_score":0.96295345},"labels":[],"label_agreement":null},{"id":"W4286500577","doi":"10.1111/stan.12275","title":"Usual stochastic ordering of the sample maxima from dependent distribution‐free random variables","year":2022,"lang":"en","type":"article","venue":"Statistica Neerlandica","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":"McMaster University","funders":"Anhui Office of Philosophy and Social Science","keywords":"Mathematics; Maxima; Majorization; Order statistic; Stochastic ordering; Distribution (mathematics); Applied mathematics; Scale (ratio); Statistical physics; Statistics; Combinatorics; Mathematical analysis","score_opus":0.030036837139877114,"score_gpt":0.29260177539951043,"score_spread":0.26256493825963334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286500577","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":[0.09122166,0.00054733385,0.8999908,0.0004000864,0.0000626413,0.00010277274,0.00027804056,0.0001984612,0.007198237],"genre_scores_gemma":[0.81332284,0.00077210146,0.17995553,0.00024782371,0.00028698088,0.00044025923,0.0007963448,0.000242103,0.003936011],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9961467,0.0014897079,0.0002190765,0.0008222058,0.0010351861,0.00028717145],"domain_scores_gemma":[0.9688028,0.023677275,0.002602547,0.0019375369,0.0020256492,0.00095406384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009451647,0.000933621,0.0011597069,0.0027177292,0.0008418771,0.002200846,0.0015520413,0.0009834386,0.0047068796],"category_scores_gemma":[0.043913923,0.0006464463,0.0012260572,0.0015223165,0.0031132735,0.0048199203,0.002082615,0.0022303266,0.00034545123],"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":[0.00016391455,0.00006502485,0.0038670276,0.00026939585,0.00007839889,0.0003933889,0.0003560739,0.040919323,0.0045980006,0.9302406,0.00096496585,0.01808399],"study_design_scores_gemma":[0.0000565823,0.00019370024,0.0075144647,0.0000774887,0.00005443761,0.00046304235,0.00017373945,0.38821232,0.0056809504,0.5938536,0.0036085309,0.00011123396],"about_ca_topic_score_codex":0.00071398553,"about_ca_topic_score_gemma":0.0008830648,"teacher_disagreement_score":0.009451647,"about_ca_system_score_codex":0.0015169197,"about_ca_system_score_gemma":0.0015559263,"threshold_uncertainty_score":0.049985647},"labels":[],"label_agreement":null},{"id":"W4308393630","doi":"10.1111/stan.12283","title":"Prior effective sample size in phase II clinical trials with mixed binary and continuous responses","year":2022,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":0,"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 de Montréal","funders":"","keywords":"Sample size determination; Binary number; Phase (matter); Statistics; Mathematics; Binary data; Set (abstract data type); Sample (material); Coronavirus disease 2019 (COVID-19); Clinical trial; Continuous phase modulation; Computer science; Medicine; Internal medicine; Physics; Chemistry; Chromatography","score_opus":0.38248530851437895,"score_gpt":0.5807419879171977,"score_spread":0.19825667940281871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308393630","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015202014,0.0024179688,0.9792636,0.0009916461,0.000115049406,0.00053141493,0.00013302201,0.00019022153,0.0011551871],"genre_scores_gemma":[0.46214253,0.0018739856,0.52902603,0.00085786387,0.0004659186,0.0035905982,0.0005176063,0.00015886141,0.0013666848],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.94577444,0.04767632,0.001386846,0.0026976732,0.002086677,0.00037802334],"domain_scores_gemma":[0.5493749,0.43550617,0.0057764933,0.0057583926,0.00258933,0.0009947711],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.110476166,0.0014297257,0.004270679,0.0033475696,0.00067730265,0.0021426904,0.0023187932,0.0029247412,0.0023282187],"category_scores_gemma":[0.29604033,0.0009956581,0.0014833629,0.0015739085,0.0038123217,0.0031951107,0.002019304,0.0039273407,0.00028835837],"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":[0.0040452518,0.0004410894,0.010878604,0.0027057184,0.0010989531,0.0007367088,0.00079515734,0.38575727,0.003386586,0.22195712,0.00446756,0.36373],"study_design_scores_gemma":[0.00075568195,0.001112142,0.0031897456,0.0005276258,0.00029250115,0.00035647585,0.00012792928,0.7028463,0.0025923029,0.28483987,0.0032876208,0.00007183262],"about_ca_topic_score_codex":0.00047475152,"about_ca_topic_score_gemma":0.00058395823,"teacher_disagreement_score":0.88952386,"about_ca_system_score_codex":0.0015926447,"about_ca_system_score_gemma":0.0022758208,"threshold_uncertainty_score":0.5842608},"labels":[],"label_agreement":null},{"id":"W4387641884","doi":"10.1111/stan.12328","title":"Asymptotic comparison of negative multinomial and multivariate normal experiments","year":2023,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","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":"Université de Montréal; Université du Québec à Montréal; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Multinomial distribution; Mathematics; Multivariate statistics; Multivariate normal distribution; Statistics; Logarithm; Hellinger distance; Covariance; Mathematical analysis","score_opus":0.19219449486733747,"score_gpt":0.504022000913631,"score_spread":0.31182750604629356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387641884","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":[0.05348424,0.000615921,0.9422972,0.00028060065,0.00005281736,0.000081343955,0.000044134173,0.00025843584,0.0028852017],"genre_scores_gemma":[0.7241922,0.00061869575,0.26935282,0.0003649196,0.000121640864,0.000478379,0.00020934579,0.0002040383,0.004458022],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98810554,0.0076942826,0.00031893692,0.0015458866,0.0020071545,0.0003281507],"domain_scores_gemma":[0.8754904,0.11022242,0.0034003453,0.0076809777,0.002294918,0.00091087166],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03427379,0.00076957047,0.0013453945,0.001276561,0.00042896857,0.0013034764,0.002263706,0.00094524655,0.003197189],"category_scores_gemma":[0.14030387,0.00047368833,0.0007122108,0.000608246,0.0041672233,0.0033749796,0.0025762622,0.0021497142,0.00028500037],"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":[0.0021856073,0.00033180584,0.0073540183,0.0007264582,0.00021450769,0.00023771173,0.00069639756,0.21947035,0.022039339,0.5910355,0.0011575328,0.15455085],"study_design_scores_gemma":[0.000089111134,0.00072904106,0.0051669325,0.000110212735,0.00007656138,0.00021644603,0.000097262586,0.71233535,0.009026531,0.26968884,0.0023876198,0.00007599057],"about_ca_topic_score_codex":0.0010062668,"about_ca_topic_score_gemma":0.0009262282,"teacher_disagreement_score":0.03427379,"about_ca_system_score_codex":0.0023464742,"about_ca_system_score_gemma":0.0012790558,"threshold_uncertainty_score":0.18125927},"labels":[],"label_agreement":null},{"id":"W4400368343","doi":"10.1111/stan.12344","title":"A note on trigonometric regression in the presence of Berkson‐type measurement error","year":2024,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":5,"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 British Columbia","funders":"U.S. Department of Energy","keywords":"Mathematics; Statistics; Covariate; Residual; Trigonometry; Mean squared error; Observational error; Regression analysis; Regression; Applied mathematics; Mathematical analysis; Algorithm","score_opus":0.19113150598537218,"score_gpt":0.45115095156735147,"score_spread":0.2600194455819793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400368343","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":[0.008923829,0.001973265,0.97685903,0.0055126087,0.00097036717,0.00003365008,0.00007834892,0.00032079915,0.005328176],"genre_scores_gemma":[0.42147365,0.0061488296,0.54143804,0.007285639,0.0044707223,0.000325254,0.00031167633,0.001194991,0.017351272],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.95621705,0.030107094,0.0018149407,0.004697947,0.0063792374,0.00078377366],"domain_scores_gemma":[0.6409953,0.31474409,0.01295928,0.020399913,0.01015273,0.0007486411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.08339221,0.0019542861,0.0024337845,0.0011688587,0.0013811127,0.002786854,0.0022451293,0.0039473055,0.0028611068],"category_scores_gemma":[0.3134224,0.0008700586,0.0018087426,0.003048855,0.006427676,0.007844399,0.0034410788,0.007347691,0.0012494113],"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":[0.0003828867,0.00009909843,0.016980259,0.000587622,0.0005924186,0.003258615,0.001636964,0.1042455,0.0033920638,0.7293959,0.018381832,0.12104683],"study_design_scores_gemma":[0.000067613386,0.00033637977,0.006647613,0.0003724413,0.0003187855,0.0015371998,0.00030754332,0.47026488,0.0069258753,0.47845638,0.034470726,0.00029454456],"about_ca_topic_score_codex":0.008460678,"about_ca_topic_score_gemma":0.0043756114,"teacher_disagreement_score":0.08339221,"about_ca_system_score_codex":0.0020305493,"about_ca_system_score_gemma":0.0020793392,"threshold_uncertainty_score":0.44102544},"labels":[],"label_agreement":null},{"id":"W4407584026","doi":"10.1111/stan.70004","title":"A note on bayesian nonparametric survival function estimators for combined cohort data","year":2025,"lang":"en","type":"article","venue":"Statistica Neerlandica","topic":"Statistical Methods and Inference","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 Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Estimator; Nonparametric statistics; Statistics; Mathematics; Survival function; Bayesian probability; Cohort; Function (biology); Econometrics; Biology","score_opus":0.0703872921934794,"score_gpt":0.40203876472838135,"score_spread":0.33165147253490196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407584026","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":[0.0003790226,0.0015316322,0.99644417,0.0005677926,0.00017024751,0.000019787843,0.00007015661,0.000061067854,0.0007560835],"genre_scores_gemma":[0.024514742,0.0054282225,0.9639417,0.0010116767,0.0016613828,0.00045529532,0.00037575353,0.00020306041,0.0024081413],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.97649837,0.016660452,0.0010192526,0.0014861247,0.0040585157,0.00027731096],"domain_scores_gemma":[0.9164132,0.072916344,0.0015508748,0.0055764415,0.0032235458,0.00031954903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.056726564,0.001241293,0.001965737,0.0025691004,0.00061296084,0.002194616,0.0030665945,0.002726896,0.0022538987],"category_scores_gemma":[0.12084253,0.001244586,0.002939352,0.0029993027,0.002630484,0.00465507,0.0029101532,0.008245981,0.0012775165],"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":[0.000061635896,0.00006352946,0.0017928247,0.0003473256,0.0002836782,0.00021187254,0.0003193548,0.018188538,0.00092952175,0.8140419,0.012455795,0.15130405],"study_design_scores_gemma":[0.00006044972,0.00010418572,0.0016886137,0.00043771951,0.00014192869,0.0004926905,0.000049075585,0.16690087,0.0010905223,0.76301295,0.065886006,0.00013493386],"about_ca_topic_score_codex":0.002787522,"about_ca_topic_score_gemma":0.0027486742,"teacher_disagreement_score":0.056726564,"about_ca_system_score_codex":0.0010689487,"about_ca_system_score_gemma":0.002382338,"threshold_uncertainty_score":0.30000234},"labels":[],"label_agreement":null}]}