{"id":"W4384455411","doi":"10.32942/x27g78","title":"When indices disagree: facing conceptual and practical challenges","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Uncorrelated; Computer science; Data science; Statistical hypothesis testing; Econometrics; Key (lock); Management science; Statistics; Mathematics; Economics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.4178123,0.002311112,0.006363055,0.01183325,0.008007106,0.02795829,0.01337115,0.01363555,0.008346656],"category_scores_gemma":[0.7732667,0.002464504,0.002467811,0.01240218,0.05061178,0.05196862,0.01791355,0.02315213,0.002638026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006125271,"about_ca_system_score_gemma":0.008887087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002609763,"about_ca_topic_score_gemma":0.001730689,"domain_scores_codex":[0.6857534,0.223795,0.02382072,0.02430494,0.0394228,0.002903114],"domain_scores_gemma":[0.1976023,0.6354592,0.02581035,0.07900667,0.05668129,0.00544026],"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":[0.0002466918,0.0001091186,0.005683638,0.0006553826,0.0003006182,0.0003835515,0.007376311,0.001630621,0.0003305227,0.8181076,0.03678618,0.1283897],"study_design_scores_gemma":[0.00005138293,0.00002016657,0.0005283916,0.0002924799,0.00002031931,0.00009949154,0.001435773,0.003126143,0.0001958343,0.9836584,0.01052131,0.00005044242],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02114284,0.008574945,0.6226109,0.3040514,0.007916473,0.0006779081,0.001110342,0.001537253,0.03237788],"genre_scores_gemma":[0.2757257,0.003195092,0.6671762,0.03790343,0.009177496,0.002613484,0.0009669449,0.001148348,0.002093219],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4178123,"threshold_uncertainty_score":0.7179411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1811186444060587,"score_gpt":0.3287735702544623,"score_spread":0.1476549258484036,"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."}}