{"id":"W2169080987","doi":"10.1897/ieam_2007-002.1","title":"Evaluating consistency of best professional judgment in the application of a multiple lines of evidence sediment quality triad","year":2007,"lang":"en","type":"article","venue":"Integrated Environmental Assessment and Management","topic":"Environmental Toxicology and Ecotoxicology","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Island University; Golder Associates (Canada)","funders":"","keywords":"Categorical variable; Consistency (knowledge bases); Ranking (information retrieval); Statistics; Quality (philosophy); Interpretation (philosophy); Sediment; Computer science; Mathematics; Machine learning; Artificial intelligence; Geology","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":["metaresearch"],"category_scores_codex":[0.3848417,0.001250028,0.00255229,0.01475687,0.003010179,0.006897659,0.003706168,0.002829072,0.001262453],"category_scores_gemma":[0.6503612,0.001284229,0.003058302,0.007220533,0.003913464,0.004619527,0.00781023,0.002643519,0.0004667851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004412302,"about_ca_system_score_gemma":0.006011717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004018192,"about_ca_topic_score_gemma":0.008903554,"domain_scores_codex":[0.5788153,0.2246029,0.09777399,0.01785279,0.07737574,0.003579227],"domain_scores_gemma":[0.2061199,0.4947366,0.09047463,0.02903931,0.1745443,0.005085319],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006211737,0.001215708,0.5772837,0.00577211,0.007759963,0.0008236045,0.04211269,0.01005672,0.007882326,0.004144824,0.009804972,0.3269316],"study_design_scores_gemma":[0.001763532,0.008747895,0.7399998,0.008139442,0.005848187,0.002114868,0.03787896,0.09802491,0.02367462,0.03219767,0.03943425,0.002175861],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8078176,0.007832794,0.1499272,0.003057931,0.001318397,0.006012122,0.0008383486,0.0004138347,0.02278186],"genre_scores_gemma":[0.8352221,0.0009533023,0.1589077,0.0006390754,0.0002488789,0.002718076,0.000498338,0.00008649103,0.000726069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6151583,"threshold_uncertainty_score":0.7585996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1128878109106349,"score_gpt":0.4168850374463267,"score_spread":0.3039972265356918,"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."}}