{"id":"W2054205648","doi":"10.1139/z01-139","title":"Population estimation with sparse data: the role of estimators versus indices revisited","year":2001,"lang":"en","type":"article","venue":"Canadian Journal of Zoology","topic":"Census and Population Estimation","field":"Mathematics","cited_by":133,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Estimator; Statistics; Population; Biology; Variance (accounting); Estimation; Index (typography); Econometrics; Mathematics; Demography; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000489119,0.00008770272,0.0002189773,0.0002254385,0.0001086605,0.00002078734,0.0002538286,0.00007089628,0.0001073981],"category_scores_gemma":[0.0006866056,0.00006044279,0.00002886048,0.0002434082,0.0000729915,0.0002873648,0.0000105009,0.000136863,0.000003379214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006827052,"about_ca_system_score_gemma":0.0002421397,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003400892,"about_ca_topic_score_gemma":0.03629978,"domain_scores_codex":[0.9990771,0.00008975071,0.0004460521,0.00008708606,0.0001504524,0.0001495398],"domain_scores_gemma":[0.9984137,0.0002631566,0.0007082985,0.0002991497,0.0001840347,0.0001316664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000271435,0.00002788571,0.9209279,0.00003947625,0.0001283429,0.00004923335,0.0008265554,0.004988542,0.0000156943,0.03471907,0.0007606863,0.03724521],"study_design_scores_gemma":[0.001796639,0.0004707584,0.8562067,0.0002295613,0.000467591,0.0009773835,0.0004872764,0.07391495,0.00004148976,0.06152379,0.003636166,0.0002477541],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942786,0.0002812048,0.004068518,0.0004970134,0.0002106985,0.0001257907,0.0000219289,0.000006005902,0.0005102113],"genre_scores_gemma":[0.9875106,0.000008712796,0.01227323,0.00002593296,0.00008412097,7.147339e-7,0.00007308218,0.00001119865,0.00001243838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0689264,"threshold_uncertainty_score":0.9812852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05841668197180536,"score_gpt":0.3116214565361938,"score_spread":0.2532047745643885,"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."}}