{"id":"W4255072394","doi":"10.1515/iupac.79.1713","title":"Occupational Exposure Limit (OEL)","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemical Safety and Risk Management","field":"Chemical Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Occupational exposure limit; Hazard; Toxicology; Computer science; Occupational exposure; Medicine; Chemistry; Environmental health; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002586265,0.0005085153,0.0005692951,0.0001204394,0.00008888252,0.00003706965,0.0005975821,0.0005410757,0.00889696],"category_scores_gemma":[0.0004883673,0.0003782581,0.0002807694,0.0001721415,0.00009195403,0.00008430955,0.0003534371,0.0006618282,0.00002151752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005672469,"about_ca_system_score_gemma":0.0002281219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005812123,"about_ca_topic_score_gemma":0.00009917235,"domain_scores_codex":[0.9970469,0.00002608779,0.0005875935,0.0005861214,0.001237384,0.0005158539],"domain_scores_gemma":[0.9983685,0.0001701432,0.0001959349,0.0007961073,0.0002375053,0.0002318123],"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":[0.0002179274,0.0001871704,0.000004851069,0.0002471131,0.0001417252,0.00003864075,0.000003789923,0.00004644416,0.0002533096,0.00007902629,0.9952602,0.003519835],"study_design_scores_gemma":[0.0009786212,0.0000643546,0.00001893171,0.0003827667,0.0001279642,0.000004733421,0.0000049399,0.00006136895,0.0003594433,0.000134938,0.9973118,0.0005500786],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005505295,0.0006538274,0.001752548,0.000701166,0.0006687607,0.0002156654,0.9956219,0.0001690567,0.0001620895],"genre_scores_gemma":[0.00007451022,0.001042114,0.0001138596,0.000292828,0.002036512,0.00002523692,0.9949812,0.0000511884,0.001382495],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.008875443,"threshold_uncertainty_score":0.999867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01326962758782376,"score_gpt":0.3515481715637904,"score_spread":0.3382785439759667,"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."}}