{"id":"W4242718851","doi":"10.1515/iupac.79.1704","title":"Nosocomial","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Hazard; Multidisciplinary approach; Toxicology; Chemistry; Philosophy; Biology; Linguistics; Political science; Law; 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":[0.001198279,0.001192237,0.00165201,0.002565208,0.00072632,0.002787831,0.002137264,0.001350412,0.2184927],"category_scores_gemma":[0.01454934,0.0005042609,0.001355704,0.005305625,0.0002730685,0.001915854,0.001914623,0.001535011,0.1621646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001214726,"about_ca_system_score_gemma":0.003636524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01219148,"about_ca_topic_score_gemma":0.01851649,"domain_scores_codex":[0.9977512,0.0003616786,0.0004707685,0.0007873321,0.0003957397,0.0002333099],"domain_scores_gemma":[0.9949849,0.001466573,0.0007977466,0.001333019,0.001036158,0.0003815501],"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":[0.0002467497,0.0000193431,0.002260717,0.001517353,0.00006602832,0.00003601405,0.00002027986,0.0001431033,0.00005866366,0.0007986806,0.9847485,0.01008449],"study_design_scores_gemma":[0.0003173029,0.00002048525,0.004225967,0.000871166,0.00006523667,0.0001085382,0.00005561273,0.0001960361,0.0001452254,0.001894548,0.9920739,0.00002590871],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001504955,0.000190144,0.0001106846,0.0001036788,0.00005088549,0.00003733799,0.9963335,0.000241636,0.002781601],"genre_scores_gemma":[0.001116777,0.0002676275,0.0003822605,0.0002924622,0.00003261452,0.0002177029,0.9948554,0.0001361208,0.002699024],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2184927,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01277107049199018,"score_gpt":0.3906749234600166,"score_spread":0.3779038529680264,"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."}}