{"id":"W4238801181","doi":"10.1515/iupac.88.1451","title":"Tympanic","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008805903,0.00147764,0.001369419,0.003583657,0.0007747706,0.002507491,0.001692635,0.001272355,0.1952518],"category_scores_gemma":[0.01039068,0.0004754585,0.001610551,0.005361872,0.0004059552,0.002455,0.002209996,0.001465171,0.1546995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001166592,"about_ca_system_score_gemma":0.002176082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01294129,"about_ca_topic_score_gemma":0.01896048,"domain_scores_codex":[0.9985342,0.0002111761,0.0004156927,0.0004025614,0.0002967108,0.0001396357],"domain_scores_gemma":[0.9959357,0.001333502,0.0006497899,0.0007455297,0.00115987,0.0001757073],"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":[0.0003388531,0.00001978137,0.003089696,0.003865246,0.00006231139,0.00008813131,0.00005775247,0.0002479154,0.0002481382,0.001272212,0.9655325,0.02517758],"study_design_scores_gemma":[0.0001838258,0.00003274084,0.01039477,0.0021455,0.00006106891,0.0002999603,0.0001878738,0.0002370954,0.0002878608,0.002322294,0.9838045,0.00004241107],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003914087,0.0004695193,0.0002459747,0.0001320116,0.000092478,0.00004684371,0.993718,0.0002765415,0.004627237],"genre_scores_gemma":[0.001950018,0.0007939256,0.0007942209,0.0002954161,0.00005250471,0.0002325493,0.9917951,0.0001414266,0.003944785],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8047482,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02508972046446419,"score_gpt":0.4681845136245413,"score_spread":0.4430947931600772,"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."}}