{"id":"W4254703693","doi":"10.1515/iupac.88.1266","title":"Pulmonary Artery","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Pulmonary Hypertension Research and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Computer science; Linguistics; 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":[0.0007470061,0.001021882,0.001314753,0.00272916,0.000525024,0.002078309,0.001518624,0.001375667,0.09475493],"category_scores_gemma":[0.009142788,0.0003853207,0.001466155,0.004492015,0.0002576401,0.001743797,0.001327652,0.001731882,0.06343231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008279265,"about_ca_system_score_gemma":0.001946425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008996841,"about_ca_topic_score_gemma":0.01379442,"domain_scores_codex":[0.9989512,0.000151139,0.0002544683,0.0003514598,0.0001855294,0.0001061449],"domain_scores_gemma":[0.9964444,0.001119084,0.000675112,0.0007077586,0.0008506989,0.0002029577],"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":[0.0004911573,0.00002855216,0.009005349,0.005008381,0.0001778891,0.0001524356,0.00004142696,0.0002996883,0.0002388595,0.00156686,0.9524581,0.03053135],"study_design_scores_gemma":[0.0004160421,0.00004536124,0.02515944,0.00372444,0.000203378,0.0006851659,0.0001000295,0.0004337393,0.0004136852,0.003822128,0.9649401,0.0000564917],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005562659,0.001078963,0.0003494316,0.0002446631,0.0001000541,0.00006909553,0.9913606,0.0003203191,0.005920629],"genre_scores_gemma":[0.003112705,0.001380061,0.001066638,0.0005209025,0.0001075473,0.0003614258,0.989883,0.00009595554,0.003471788],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09475493,"threshold_uncertainty_score":0.3169869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03250093801705379,"score_gpt":0.4476555548227948,"score_spread":0.4151546168057411,"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."}}