{"id":"W4248636058","doi":"10.1515/iupac.79.1488","title":"Initiator","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; Library science; 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":[0.001644076,0.0017092,0.001513236,0.003403033,0.001098896,0.003680038,0.002512089,0.001798616,0.2379508],"category_scores_gemma":[0.01417718,0.0006049572,0.001861047,0.005969724,0.0003522313,0.002581373,0.002150639,0.001850326,0.2863849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00174122,"about_ca_system_score_gemma":0.003242812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01684441,"about_ca_topic_score_gemma":0.02754094,"domain_scores_codex":[0.997454,0.0004157782,0.0004048246,0.0009199326,0.0005098955,0.0002955034],"domain_scores_gemma":[0.9943112,0.001396995,0.0005254907,0.001481617,0.00192932,0.0003554012],"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":[0.00012461,0.00001772589,0.001334404,0.0007619314,0.00003054816,0.00001498915,0.00002189373,0.0001121509,0.00006539695,0.0007409509,0.9898105,0.00696488],"study_design_scores_gemma":[0.0001628657,0.0000170715,0.00294273,0.0005132079,0.00003775382,0.00005028192,0.0000886077,0.0001584044,0.0001588724,0.001543132,0.9943052,0.00002180177],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001202742,0.0001020105,0.0001145329,0.00009998675,0.00004668638,0.00003425049,0.9969085,0.0002621853,0.002311569],"genre_scores_gemma":[0.0004757931,0.0001120332,0.000406806,0.0001974593,0.00001829779,0.0001894965,0.9960667,0.0001009644,0.002432382],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2379508,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02054807898548029,"score_gpt":0.4332200301319247,"score_spread":0.4126719511464444,"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."}}