{"id":"W2098243005","doi":"10.1111/biom.12325","title":"Mixture regression models for closed population capture–recapture data","year":2015,"lang":"en","type":"article","venue":"Biometrics","topic":"Census and Population Estimation","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Covariate; Akaike information criterion; Statistics; Mathematics; Econometrics; Inference; Estimator; Population; Random effects model; Model selection; Statistical inference; Logit; Computer science; Meta-analysis","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.0007756645,0.0001676742,0.0002254891,0.0005955191,0.0000916908,0.00005523674,0.0003144064,0.0002619611,0.000009421138],"category_scores_gemma":[0.002333016,0.0001324552,0.00005324287,0.001527537,0.00001255897,0.0004242289,0.00009871892,0.00009819538,0.000006750708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001039961,"about_ca_system_score_gemma":0.00004196284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008274594,"about_ca_topic_score_gemma":0.00002638672,"domain_scores_codex":[0.9986096,0.00004673246,0.0003565562,0.0003244202,0.0004616593,0.0002010061],"domain_scores_gemma":[0.9982194,0.0002827898,0.0002751546,0.0007571279,0.0003258864,0.0001396477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002728076,0.0004959237,0.007636472,0.0005227876,0.00007914683,0.000004942205,0.001426299,0.001663902,0.0002902163,0.156052,0.7395793,0.0919762],"study_design_scores_gemma":[0.001745362,0.00007763133,0.003157025,0.0000775127,0.0001296467,0.00001120041,0.0001039289,0.5631068,0.00008550152,0.3778415,0.05320929,0.0004546129],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07173128,0.001860718,0.9169774,0.001602054,0.002254201,0.001765355,0.001261652,0.0004386412,0.002108681],"genre_scores_gemma":[0.8212451,0.00001364234,0.1731823,0.00009767364,0.0003459012,0.00001409144,0.004292129,0.00004129332,0.0007678037],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7495139,"threshold_uncertainty_score":0.5401365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2753151171504339,"score_gpt":0.4006136085464878,"score_spread":0.1252984913960539,"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."}}