{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0139792,0.001750524,0.003125135,0.003971136,0.0009857152,0.002588656,0.00691146,0.003056945,0.00537122],"category_scores_gemma":[0.03544921,0.00194736,0.003209647,0.0048812,0.001700828,0.004630378,0.002841042,0.003818366,0.002448859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001883833,"about_ca_system_score_gemma":0.001066772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01872056,"about_ca_topic_score_gemma":0.01269119,"domain_scores_codex":[0.9942046,0.003706591,0.0002763304,0.0009974828,0.0005448115,0.0002701883],"domain_scores_gemma":[0.9781522,0.01796284,0.001519739,0.001098024,0.001051932,0.0002152964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002003245,0.00009607449,0.004073522,0.0003513718,0.0004239699,0.000263717,0.0004220853,0.6985218,0.0007508963,0.2380757,0.002465114,0.05435539],"study_design_scores_gemma":[0.00002013789,0.00002279147,0.0006281699,0.00002525727,0.00004712523,0.00006022887,0.00002038794,0.9466265,0.0000915212,0.05052068,0.001904189,0.00003310871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005623855,0.0008051632,0.9919394,0.0002142807,0.0000450077,0.00007531694,0.0003668093,0.000384587,0.000545527],"genre_scores_gemma":[0.3035657,0.004617393,0.6618205,0.0003627855,0.0004542777,0.001494698,0.004587512,0.0005608941,0.02253614],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01872056,"threshold_uncertainty_score":0.07392997,"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."}}