{"id":"W4239437136","doi":"10.1515/iupac.88.0593","title":"Chordin","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","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; Philosophy; Data mining","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":[0.001267351,0.001602591,0.00140961,0.004861183,0.001105702,0.003345351,0.002170537,0.001744897,0.1504599],"category_scores_gemma":[0.01018941,0.0007036257,0.001451442,0.007751711,0.0004640275,0.002818573,0.00291133,0.001815318,0.1623645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001414677,"about_ca_system_score_gemma":0.002777474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01250826,"about_ca_topic_score_gemma":0.02575663,"domain_scores_codex":[0.9982888,0.000265847,0.000419213,0.0004742594,0.0003631809,0.0001885842],"domain_scores_gemma":[0.996076,0.001394644,0.0005547438,0.0008689697,0.0008528404,0.0002527445],"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":[0.0001960222,0.00001586641,0.001571536,0.003223207,0.00004191978,0.00004815601,0.0000656706,0.0001841725,0.0003574863,0.00133296,0.9836878,0.009275142],"study_design_scores_gemma":[0.0001138577,0.00001777761,0.003035745,0.0008883972,0.00002786998,0.00009730836,0.0000852888,0.0001103259,0.0002111436,0.001207623,0.9941791,0.00002549238],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001324101,0.0002712201,0.0001114729,0.0001045301,0.00004242191,0.00002276229,0.9973018,0.0002540617,0.001759283],"genre_scores_gemma":[0.0004402608,0.0002880416,0.0004710565,0.0001462868,0.00001244204,0.000117755,0.9972249,0.00009030025,0.001208861],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1504599,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02484602620358293,"score_gpt":0.4730545099692965,"score_spread":0.4482084837657136,"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."}}