{"id":"W2090853233","doi":"10.1111/j.1541-0420.2007.00767.x","title":"Multilist Population Estimation with Incomplete and Partial Stratification","year":2007,"lang":"en","type":"article","venue":"Biometrics","topic":"Census and Population Estimation","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Simon Fraser University","funders":"","keywords":"Population stratification; Computer science; Stratification (seeds); Population; Statistics; Maximization; Population size; Mark and recapture; Estimation; Econometrics; Expectation–maximization algorithm; Data mining; Mathematics; Mathematical optimization; Maximum likelihood; Demography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00389723,0.0004207613,0.0008085503,0.001017252,0.0007107683,0.0009368553,0.001339753,0.0007209064,0.001716606],"category_scores_gemma":[0.01938106,0.0003029596,0.0008240062,0.001402659,0.0005639946,0.001450716,0.002071393,0.001121501,0.0004424107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000710471,"about_ca_system_score_gemma":0.0006197385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004890503,"about_ca_topic_score_gemma":0.009306741,"domain_scores_codex":[0.9980545,0.001134083,0.00009200638,0.000367816,0.0002485156,0.0001030604],"domain_scores_gemma":[0.9927153,0.004688803,0.0006769919,0.001231022,0.0005800402,0.0001079092],"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":[0.0001227771,0.0001006649,0.03730644,0.0001658847,0.0003522005,0.000394616,0.0007607386,0.4253018,0.002632021,0.1977476,0.005224004,0.3298914],"study_design_scores_gemma":[0.00001293057,0.00002000687,0.00607996,0.00001788178,0.00002700999,0.0001543004,0.000050907,0.8808963,0.0007417899,0.1085928,0.003379481,0.0000265518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01975083,0.0001057033,0.9788801,0.0001112302,0.00001041525,0.000021046,0.0001418635,0.0001277398,0.0008510085],"genre_scores_gemma":[0.3895694,0.0002222804,0.6056021,0.0001101309,0.00004869547,0.0001671749,0.0009849415,0.00007450268,0.003220724],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004890503,"threshold_uncertainty_score":0.02061081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.081416258894013,"score_gpt":0.3580471631329333,"score_spread":0.2766309042389203,"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."}}