{"id":"W2953900668","doi":"10.1002/env.2498","title":"Partial stratification in two‐sample capture–recapture experiments","year":2018,"lang":"en","type":"article","venue":"Environmetrics","topic":"Census and Population Estimation","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Minnesota Department of Natural Resources","keywords":"Statistics; Mark and recapture; Covariate; Sampling (signal processing); Econometrics; Sample size determination; Population; Fish <Actinopterygii>; Sample (material); Mathematics; Computer science; Biology; Fishery; Demography; Filter (signal processing)","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":[0.0002600115,0.0001143796,0.000125757,0.000194558,0.00007336833,0.00002410742,0.00009656851,0.00007554371,0.0005461287],"category_scores_gemma":[0.0005659248,0.0001124412,0.00003221575,0.0004608717,0.00005133497,0.0001269537,0.00002301203,0.000108491,0.0001148309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009143085,"about_ca_system_score_gemma":0.00001083477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001624829,"about_ca_topic_score_gemma":0.0001091756,"domain_scores_codex":[0.9990073,0.00005691006,0.0003008181,0.0002090893,0.0002480355,0.0001778606],"domain_scores_gemma":[0.9992934,0.0002195628,0.0001276639,0.0002865579,0.00001929813,0.00005347719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001469677,0.002002615,0.5071246,0.0001011602,0.00006428437,0.00001399334,0.01596144,0.001663845,0.01299029,0.3717466,0.01309651,0.07508769],"study_design_scores_gemma":[0.004657622,0.000303648,0.5201862,0.00007441835,0.0001078663,0.00001617864,0.0008733876,0.09567939,0.05022525,0.2486677,0.07754704,0.001661269],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.884694,0.0001027547,0.1109126,0.0001749938,0.0003864904,0.0003497586,0.00002387667,0.00006674908,0.003288796],"genre_scores_gemma":[0.9698773,0.000006411219,0.02953312,0.00006049495,0.0002136156,0.0000162824,0.00006304406,0.00001791418,0.0002118321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1230789,"threshold_uncertainty_score":0.5979727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07460433109161382,"score_gpt":0.354532178000344,"score_spread":0.2799278469087302,"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."}}