{"id":"W4232392140","doi":"10.1515/iupac.79.2160","title":"Tracer","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":[0.001659991,0.002249405,0.001581299,0.003816542,0.001075685,0.003763019,0.003657806,0.002130275,0.1708563],"category_scores_gemma":[0.01178495,0.0006618098,0.002269875,0.005932709,0.000425226,0.002856129,0.002463447,0.002005435,0.2333337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00180027,"about_ca_system_score_gemma":0.003035973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02442228,"about_ca_topic_score_gemma":0.04660223,"domain_scores_codex":[0.9977895,0.0004030986,0.0003102894,0.0008228485,0.0004311294,0.0002430475],"domain_scores_gemma":[0.9955794,0.001182061,0.0004014251,0.001231797,0.001333053,0.0002722589],"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":[0.0001085854,0.0000211205,0.001252044,0.0008230208,0.00004529514,0.00001811732,0.00002686919,0.0002706961,0.00007476957,0.000939585,0.9887758,0.007644085],"study_design_scores_gemma":[0.0001561597,0.00001908964,0.002231513,0.0004557911,0.00004059331,0.00005136602,0.00008041731,0.0003809196,0.0001784357,0.002363283,0.9940164,0.00002603433],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001223663,0.0001268016,0.000187457,0.0001092806,0.0000489442,0.00002721688,0.9970764,0.0005794538,0.001722094],"genre_scores_gemma":[0.0003921669,0.0001034641,0.0005548269,0.0001359219,0.00001464897,0.0001278692,0.996825,0.0001414112,0.001704638],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1708563,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01755366330669342,"score_gpt":0.4306373983275414,"score_spread":0.4130837350208481,"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."}}