{"id":"W4239765873","doi":"10.1515/iupac.88.0736","title":"Endocardial Cushion","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Agricultural safety and regulations","field":"Agricultural and Biological Sciences","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":[0.001029483,0.0008245481,0.001229387,0.003808385,0.0004999878,0.001831373,0.001086878,0.0009522235,0.06682122],"category_scores_gemma":[0.01191412,0.0003521637,0.001404898,0.004269747,0.0003696298,0.00128098,0.001108431,0.001239875,0.02172252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007096474,"about_ca_system_score_gemma":0.001851902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006613739,"about_ca_topic_score_gemma":0.01257694,"domain_scores_codex":[0.9989819,0.0001769897,0.0003570734,0.0002364895,0.0001636945,0.00008386396],"domain_scores_gemma":[0.9945577,0.002367981,0.001182761,0.0009604176,0.000699713,0.000231428],"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":[0.0006492864,0.00002377758,0.01144642,0.009742979,0.0002453291,0.0004389861,0.00007697444,0.0003772165,0.0003298846,0.002469559,0.92282,0.0513796],"study_design_scores_gemma":[0.0005096934,0.00006871706,0.03368753,0.01165064,0.0003647572,0.002580276,0.0002081489,0.0005319862,0.0005170829,0.005657708,0.9441402,0.00008328241],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002153588,0.005662974,0.000951222,0.0005309514,0.0002832253,0.0002559286,0.9786876,0.0003878218,0.01108667],"genre_scores_gemma":[0.01034167,0.006044738,0.002661952,0.0008875438,0.0002429436,0.000765769,0.9745101,0.0001763822,0.004368992],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06682122,"threshold_uncertainty_score":0.2235392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01862154918435449,"score_gpt":0.369596100086044,"score_spread":0.3509745509016895,"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."}}