{"id":"W4254783478","doi":"10.1515/iupac.79.0937","title":"Biopesticide","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemistry and Chemical Engineering","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Toxicology; Computer science; Chemistry; Philosophy; Biology; Linguistics; Organic chemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.001193717,0.002060873,0.001668453,0.003952474,0.000795352,0.002582912,0.002639468,0.002075024,0.07496493],"category_scores_gemma":[0.007418714,0.0006119489,0.001985497,0.006006052,0.0003488288,0.001879484,0.00198963,0.001895053,0.09415472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001736329,"about_ca_system_score_gemma":0.003033709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01850545,"about_ca_topic_score_gemma":0.03662283,"domain_scores_codex":[0.9984431,0.0002328254,0.0002674011,0.0004876719,0.0004135054,0.0001555088],"domain_scores_gemma":[0.9970331,0.0008198527,0.0004687888,0.0006629622,0.0007934993,0.0002218276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002379525,0.00004496876,0.002146061,0.002987818,0.0001025829,0.00004733495,0.00002773112,0.0006304123,0.0002896268,0.001047519,0.9823168,0.0101212],"study_design_scores_gemma":[0.0001986107,0.00002826414,0.003857011,0.000715095,0.00006973061,0.00007744694,0.00004848961,0.0003512941,0.0003639937,0.001341819,0.9929187,0.00002948151],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001204111,0.0002000798,0.00006948684,0.0000543077,0.00002207389,0.00001571392,0.9983536,0.0001688947,0.0009954071],"genre_scores_gemma":[0.0003193656,0.0001615833,0.0003035023,0.00008187997,0.000006456569,0.00006393027,0.9983499,0.00003341477,0.0006799206],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07496493,"threshold_uncertainty_score":0.2507827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005939589934642103,"score_gpt":0.3271572118818052,"score_spread":0.3212176219471631,"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."}}