{"id":"W4246186267","doi":"10.1515/iupac.79.2115","title":"Threshold Limit Value–Short-Term Exposure Limit (TLV–STEL)","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; Toxicology; Hazard; Computer 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":[0.002584836,0.001899223,0.002122931,0.004316751,0.0005990849,0.002671449,0.00316044,0.0022036,0.0692732],"category_scores_gemma":[0.01504677,0.0007471481,0.002448185,0.006389686,0.0004543027,0.002105798,0.001913102,0.002114449,0.07698208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001890803,"about_ca_system_score_gemma":0.00328457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01701649,"about_ca_topic_score_gemma":0.0236775,"domain_scores_codex":[0.997468,0.0005138764,0.0006408874,0.0006722594,0.0005142526,0.0001907256],"domain_scores_gemma":[0.9936978,0.002317982,0.00116161,0.001239894,0.001334003,0.0002488075],"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":[0.0002531873,0.00003337854,0.002241852,0.003827705,0.0001312608,0.00003201124,0.00002279956,0.0006302076,0.0001750364,0.0007254109,0.9842598,0.00766744],"study_design_scores_gemma":[0.0005047674,0.00004578524,0.007982697,0.001439719,0.0001297907,0.00009620801,0.0000481559,0.0005333206,0.0004575975,0.002088189,0.9866073,0.00006642643],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008099262,0.0001260603,0.00009814933,0.00004549219,0.00002276633,0.00002050032,0.9989942,0.000175169,0.0004366944],"genre_scores_gemma":[0.0004524069,0.0001580741,0.0004317484,0.00009435815,0.00001181255,0.0001902618,0.9980924,0.0000582202,0.0005106707],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0692732,"threshold_uncertainty_score":0.231742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02085363230270159,"score_gpt":0.3679161643875238,"score_spread":0.3470625320848222,"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."}}