{"id":"W4254627834","doi":"10.1515/iupac.79.1270","title":"Exposure Assessment","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Occupational and environmental lung diseases","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Hazard; Toxicology; Library science; Chemistry; Philosophy; Biology; Linguistics","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":[0.002197786,0.001589053,0.001568694,0.003346576,0.0004917781,0.001814491,0.00246413,0.001465199,0.1277491],"category_scores_gemma":[0.01466219,0.0005135812,0.003318235,0.004144655,0.0002287766,0.001393228,0.001593697,0.001522938,0.07455412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001436865,"about_ca_system_score_gemma":0.0030263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01386049,"about_ca_topic_score_gemma":0.02449811,"domain_scores_codex":[0.9978524,0.0004321708,0.0004858927,0.0006853591,0.0004126311,0.0001315147],"domain_scores_gemma":[0.9950699,0.00171012,0.0006225001,0.0009421395,0.001461753,0.000193533],"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":[0.0004087535,0.0000701095,0.006601242,0.005380503,0.0003888358,0.00006137319,0.00004326016,0.001366792,0.0001978079,0.001258852,0.9502006,0.03402195],"study_design_scores_gemma":[0.0003627195,0.00005631623,0.008963596,0.001499262,0.0002439528,0.0001324691,0.00007045056,0.0006038564,0.0003248177,0.002615622,0.9850817,0.00004526768],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002181799,0.0002315365,0.0003747443,0.00007263503,0.00003162709,0.00008335863,0.996904,0.0002295621,0.001854435],"genre_scores_gemma":[0.001344576,0.000319475,0.001382851,0.0002106645,0.00002368866,0.0004981346,0.9936615,0.00008209931,0.002476948],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1277491,"threshold_uncertainty_score":0.4273632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01205063582013374,"score_gpt":0.4167926035946647,"score_spread":0.404741967774531,"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."}}