{"id":"W4389513713","doi":"10.1002/cjs.11801","title":"Modelling occurrence and quantity of longitudinal semicontinuous data simultaneously with nonparametric unobserved heterogeneity","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Covariate; Nonparametric statistics; Econometrics; Longitudinal data; Statistics; Mathematics; Poisson distribution; Mixed model; Population; Random effects model; Sequence (biology); Correlation; Computer science; Biology; Data mining; Demography; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008338211,0.0001603458,0.0004799216,0.0003009653,0.0001012198,0.0000697799,0.0004261876,0.00006404526,0.00002741069],"category_scores_gemma":[0.003858061,0.0001341181,0.0000239819,0.0005730219,0.0002626928,0.00012134,0.00004711653,0.0002714815,0.000002275268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004023422,"about_ca_system_score_gemma":0.000718947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002368444,"about_ca_topic_score_gemma":0.009472023,"domain_scores_codex":[0.9984556,0.0001046846,0.0006055513,0.0002144449,0.0002848711,0.0003348376],"domain_scores_gemma":[0.9953642,0.00277976,0.0004704899,0.0003674429,0.000537025,0.0004810878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004437592,0.0002551997,0.3966888,0.003122692,0.0009865868,0.0103219,0.001748595,0.01601026,0.0001779919,0.4448861,0.01858159,0.1067765],"study_design_scores_gemma":[0.001360602,0.001178474,0.01389899,0.0008632296,0.0006541869,0.0009553713,0.0003688426,0.6919855,0.0001865199,0.2873996,0.0003989068,0.0007496614],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.242891,0.0001075738,0.7526593,0.00001961656,0.00009837292,0.00007514789,0.004128382,0.000006222911,0.00001439986],"genre_scores_gemma":[0.4912524,0.0000557692,0.5086297,0.000006477843,0.00002064057,3.370599e-7,0.00002071805,0.000009914955,0.000003988516],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6759753,"threshold_uncertainty_score":0.5469176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1928218269499876,"score_gpt":0.3585829582406329,"score_spread":0.1657611312906453,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}