{"id":"W2996410419","doi":"10.1111/biom.13185","title":"On continuous‐time capture‐recapture in closed populations","year":2019,"lang":"en","type":"letter","venue":"Biometrics","topic":"Census and Population Estimation","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Actua; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mark and recapture; Poisson distribution; Discretization; Bernoulli's principle; Computer science; Sampling (signal processing); Statistics; Discrete time and continuous time; Population size; Population; Mathematics; Econometrics; Applied mathematics","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":[0.008053748,0.0005422521,0.0005849389,0.001388566,0.000823357,0.001567979,0.002369019,0.004714372,0.004592403],"category_scores_gemma":[0.05594415,0.0004745789,0.0005215844,0.001772408,0.004351688,0.003956102,0.002299227,0.006525955,0.004743173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002579925,"about_ca_system_score_gemma":0.0008030173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003401712,"about_ca_topic_score_gemma":0.002542453,"domain_scores_codex":[0.99446,0.003017159,0.0002463909,0.0007404113,0.001402664,0.0001334137],"domain_scores_gemma":[0.9693728,0.02390101,0.001378668,0.003155904,0.001926579,0.0002649224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001854041,0.00004322941,0.004396704,0.0004472486,0.00006660316,0.001562249,0.0004696025,0.01776122,0.001072182,0.4239838,0.1327343,0.4172775],"study_design_scores_gemma":[0.00005350706,0.00007422602,0.003403215,0.0003309596,0.00002118704,0.002461154,0.0001163627,0.07002407,0.0008994477,0.7503627,0.1721822,0.00007086156],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009003772,0.01260948,0.7804623,0.1508531,0.006013267,0.0001098002,0.0004848614,0.0006366245,0.03982697],"genre_scores_gemma":[0.4403898,0.03454908,0.3480024,0.09120159,0.02329632,0.0008987708,0.0007735578,0.000545965,0.06034245],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008053748,"threshold_uncertainty_score":0.04259282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07591859289225492,"score_gpt":0.3259205004281728,"score_spread":0.2500019075359179,"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."}}