{"id":"W626264310","doi":"","title":"Variance estimation for richness measures","year":2013,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Species richness; Econometrics; Inference; Variance (accounting); Statistics; Earnings; Sample (material); Sampling (signal processing); Mathematics; Monte Carlo method; Computer science; Economics; Ecology; Artificial intelligence","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":[0.008785285,0.0008594024,0.000927921,0.003567658,0.0005078434,0.001551278,0.001411033,0.0007999677,0.002853032],"category_scores_gemma":[0.05862489,0.000560974,0.001694391,0.001985873,0.001221222,0.002244743,0.001728892,0.002508799,0.0007817555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009021058,"about_ca_system_score_gemma":0.000618378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001667719,"about_ca_topic_score_gemma":0.001311725,"domain_scores_codex":[0.9926817,0.004074489,0.0003175448,0.00115347,0.001491769,0.0002811113],"domain_scores_gemma":[0.9666275,0.02685281,0.001455095,0.003017349,0.00188619,0.0001609857],"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":[0.0001419648,0.0001161974,0.02231164,0.0006649464,0.0008328969,0.000284286,0.001086177,0.1400052,0.01160797,0.5068297,0.005859078,0.31026],"study_design_scores_gemma":[0.00003765124,0.0001525392,0.0170663,0.0002229139,0.0001402378,0.0004793826,0.0002678201,0.5335585,0.01102827,0.422376,0.01452402,0.0001463088],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005926577,0.0001933623,0.9928014,0.00005466922,0.00002634668,0.00002872087,0.0001070821,0.00013806,0.0007237421],"genre_scores_gemma":[0.3362843,0.001060075,0.6557572,0.000226812,0.0004016109,0.0006255396,0.002325278,0.0006169266,0.002702219],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008785285,"threshold_uncertainty_score":0.04646164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08268143567247742,"score_gpt":0.3849231727561611,"score_spread":0.3022417370836836,"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."}}