{"id":"W4244979934","doi":"10.1515/iupac.79.1318","title":"Gavage","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; 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":[0.001433966,0.001928501,0.001910712,0.004393874,0.0009560657,0.004262596,0.002997575,0.001863377,0.1966131],"category_scores_gemma":[0.01061789,0.0007537032,0.001780271,0.0083961,0.0004140044,0.003115223,0.003099547,0.002029231,0.2948359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001304231,"about_ca_system_score_gemma":0.002685183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0141438,"about_ca_topic_score_gemma":0.02727097,"domain_scores_codex":[0.9982662,0.0003516519,0.0002608934,0.0005708176,0.0003406318,0.000209938],"domain_scores_gemma":[0.9964288,0.0009311073,0.0004497764,0.0009813701,0.0008796022,0.0003293109],"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":[0.00008959165,0.00001284582,0.000887284,0.0009386095,0.00003774711,0.00001497007,0.00002761596,0.0001581384,0.00007372419,0.000720553,0.9922211,0.004817944],"study_design_scores_gemma":[0.0001249797,0.00001170201,0.001366474,0.0003974762,0.00002349913,0.00003255072,0.00004612944,0.0001319687,0.0001041875,0.001267695,0.9964768,0.00001661314],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006566528,0.0001180077,0.00008346888,0.00007762331,0.00002671489,0.00001450761,0.9978179,0.0004620687,0.001334075],"genre_scores_gemma":[0.0002516395,0.0001476402,0.0003133049,0.0001118559,0.00001121457,0.00009020822,0.9976195,0.0001642194,0.001290556],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1966131,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01670694009396108,"score_gpt":0.4271957960469961,"score_spread":0.4104888559530351,"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."}}