{"id":"W7095314690","doi":"","title":"Estimation of population size from biased samples using non-parametric binary regression. Statistica Sinica","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Estimator; Sampling (signal processing); Covariate; Abundance estimation; Population; Smoothing; Population size; Sample size determination; Kernel (algebra)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02877619,0.000503914,0.001376978,0.001809434,0.0003718013,0.0009058391,0.002140196,0.001137601,0.001990431],"category_scores_gemma":[0.1252307,0.0004616569,0.0009315193,0.001458033,0.001819967,0.001251196,0.001443732,0.001502145,0.0004787114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008507043,"about_ca_system_score_gemma":0.0006672773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002266467,"about_ca_topic_score_gemma":0.002294728,"domain_scores_codex":[0.9856075,0.01137548,0.0004325008,0.001290838,0.001137832,0.0001558404],"domain_scores_gemma":[0.922876,0.06137665,0.005813875,0.007163909,0.002513422,0.0002561706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001084558,0.000293381,0.1016117,0.001738911,0.001792671,0.0004115448,0.0007544769,0.1585235,0.01284503,0.100463,0.006532586,0.6139488],"study_design_scores_gemma":[0.0001548606,0.0002082568,0.04196943,0.0001724525,0.0002402857,0.0003459105,0.00008903649,0.855792,0.007686171,0.0880008,0.005262766,0.0000780104],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03929334,0.0006479839,0.9588248,0.0001609904,0.00007340746,0.00009364884,0.0002585723,0.0002903629,0.000356846],"genre_scores_gemma":[0.4725497,0.0004286767,0.5231339,0.0002395175,0.00008318904,0.0007219745,0.0009739684,0.0001644898,0.001704583],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02877619,"threshold_uncertainty_score":0.1521848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05778569613823359,"score_gpt":0.3013149440289047,"score_spread":0.2435292478906711,"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."}}