{"id":"W4246416536","doi":"10.1515/iupac.88.1093","title":"Myocardium","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; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001844534,0.001460198,0.001345264,0.003950372,0.001070022,0.004018432,0.00250657,0.001913582,0.2700309],"category_scores_gemma":[0.01776752,0.0006516963,0.001768005,0.00740382,0.0004252294,0.003517322,0.002684305,0.001850525,0.2776856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002017481,"about_ca_system_score_gemma":0.003781358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01785786,"about_ca_topic_score_gemma":0.02851665,"domain_scores_codex":[0.9968793,0.0005093782,0.0006618969,0.0009513086,0.0006689415,0.0003291771],"domain_scores_gemma":[0.992447,0.001872022,0.0007508622,0.001725948,0.002802103,0.0004019498],"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":[0.00008568154,0.00001103335,0.0008790091,0.001013555,0.00002181903,0.00001378775,0.00002545712,0.00007015286,0.00005829937,0.001014548,0.9896388,0.007167849],"study_design_scores_gemma":[0.00009460949,0.0000120897,0.002375539,0.0007928215,0.00001994021,0.00004510767,0.0000775709,0.00008887841,0.00011888,0.001338983,0.9950163,0.0000193425],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009988002,0.0001261337,0.0001293446,0.0001597274,0.00006481905,0.00004082733,0.995589,0.0002676637,0.0035226],"genre_scores_gemma":[0.0004095556,0.0001663942,0.0004181479,0.0002656726,0.00002234732,0.0001930724,0.9954814,0.0001229978,0.002920394],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7299691,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02240749459041801,"score_gpt":0.4574084196470415,"score_spread":0.4350009250566235,"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."}}