{"id":"W4256333030","doi":"10.1515/iupac.88.0950","title":"Integrin","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Academic Writing and Publishing","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Data mining; Philosophy","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":[0.001512622,0.00146211,0.001214261,0.004456496,0.001088105,0.003867807,0.002293454,0.001837875,0.213059],"category_scores_gemma":[0.01476162,0.0005750555,0.001556771,0.007371395,0.0004374155,0.003124456,0.002658813,0.001796595,0.2551715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001737401,"about_ca_system_score_gemma":0.003289838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01623016,"about_ca_topic_score_gemma":0.02871799,"domain_scores_codex":[0.9971723,0.0004522963,0.0005575056,0.0008971645,0.0006111321,0.0003096612],"domain_scores_gemma":[0.9943885,0.001351541,0.0005708011,0.001331422,0.002024887,0.0003328289],"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":[0.00006812773,0.00001328887,0.001182315,0.0009575979,0.00002170432,0.0000184137,0.00003251356,0.00008507882,0.00008032003,0.001097813,0.9887943,0.007648558],"study_design_scores_gemma":[0.00006072931,0.000009316578,0.002273472,0.0006280941,0.00001574408,0.00004771187,0.00009158437,0.00009210132,0.0001238495,0.001095093,0.9955453,0.00001697077],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00013052,0.0001531057,0.0001467907,0.0001517929,0.00007068134,0.00003829078,0.9952963,0.0002865375,0.003726122],"genre_scores_gemma":[0.0004099081,0.000159924,0.0004302151,0.0002175198,0.00002003159,0.0001639478,0.9957436,0.00009592514,0.002758979],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.213059,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0388757919897754,"score_gpt":0.4153182016634503,"score_spread":0.3764424096736749,"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."}}