{"id":"W2054663330","doi":"10.1111/j.1541-0420.2008.01129.x","title":"A Multilevel Model for Continuous Time Population Estimation","year":2009,"lang":"en","type":"article","venue":"Biometrics","topic":"Census and Population Estimation","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Estimation; Contingency table; Population; Population size; Estimator; Statistics; Computer science; Bayesian probability; Econometrics; Hierarchical database model; Statistical model; Data mining; Mathematics; Medicine","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":[0.009494001,0.0007717193,0.002132823,0.002170715,0.001082234,0.002585067,0.005359385,0.002303219,0.01212936],"category_scores_gemma":[0.03023769,0.0007694048,0.002977687,0.004424346,0.001130242,0.002897556,0.00296426,0.004882481,0.002906547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002519632,"about_ca_system_score_gemma":0.00294697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01324779,"about_ca_topic_score_gemma":0.0166444,"domain_scores_codex":[0.9921907,0.004852071,0.0003593483,0.001012106,0.001117705,0.000468148],"domain_scores_gemma":[0.9883032,0.008163331,0.0008729362,0.001028767,0.001302397,0.0003293882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001700719,0.0001150066,0.009102341,0.0003093988,0.0004664513,0.0002889453,0.0006272821,0.1226394,0.0005472666,0.7662916,0.01409271,0.08534947],"study_design_scores_gemma":[0.00009546387,0.0001517974,0.002673981,0.0001364205,0.0001732881,0.0001828014,0.0001174972,0.6511184,0.0002329062,0.3178768,0.02716291,0.00007780301],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002193169,0.0003718865,0.9928052,0.001111052,0.0001175498,0.0001120244,0.0009158424,0.000250259,0.002123143],"genre_scores_gemma":[0.1857303,0.001806771,0.7928959,0.0008511475,0.0005514926,0.002533957,0.003187469,0.0002463526,0.01219673],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01324779,"threshold_uncertainty_score":0.0502097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09696894577694708,"score_gpt":0.3672199900365666,"score_spread":0.2702510442596195,"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."}}