{"id":"W3123639107","doi":"","title":"Statistical Inference for Richness Measures","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Species richness; Inference; Econometrics; Statistics; Parametric statistics; Variance (accounting); Statistical inference; Sampling (signal processing); Mathematics; Earnings; Sample (material); Computer science; Economics; 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":[0.02934958,0.0008730961,0.001730073,0.00403562,0.0007855009,0.002598395,0.002202242,0.001306311,0.004034323],"category_scores_gemma":[0.208737,0.0008451862,0.00194973,0.002644177,0.003248252,0.005399182,0.002604469,0.003933447,0.0007080649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001326019,"about_ca_system_score_gemma":0.0007760999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001377604,"about_ca_topic_score_gemma":0.000886045,"domain_scores_codex":[0.9805751,0.01225563,0.0008708489,0.002958233,0.002914743,0.0004254093],"domain_scores_gemma":[0.8286676,0.1475091,0.007671738,0.01195842,0.003743699,0.000449466],"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":[0.000132309,0.00008467146,0.02087689,0.0006291786,0.0009479222,0.0003643088,0.0008150656,0.153109,0.002323609,0.6866079,0.003909933,0.1301993],"study_design_scores_gemma":[0.00003570363,0.0001018137,0.008741053,0.000207953,0.00009954848,0.0002653011,0.0001883259,0.3720529,0.002964511,0.6108885,0.00438047,0.00007375695],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01038279,0.0002578028,0.9874609,0.0001908337,0.00004911968,0.00004643113,0.0001789304,0.0001483488,0.001284778],"genre_scores_gemma":[0.5179897,0.001341926,0.4746942,0.0006191367,0.0006160981,0.0007544589,0.001706179,0.0003946669,0.001883701],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02934958,"threshold_uncertainty_score":0.1552173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02899017809189379,"score_gpt":0.2420253649731589,"score_spread":0.2130351868812651,"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."}}