{"id":"W4239835613","doi":"10.1515/iupac.88.0494","title":"Aortopulmonary Septum","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Cardiac, Anesthesia and Surgical Outcomes","field":"Medicine","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; Medicine; 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":[0.0006889343,0.0008184797,0.001227043,0.00281423,0.0005421976,0.001845908,0.0009694846,0.0008610516,0.07288295],"category_scores_gemma":[0.007769908,0.0003616147,0.001458998,0.003509643,0.0002590184,0.001423636,0.001149651,0.001800485,0.03213723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006616151,"about_ca_system_score_gemma":0.001753647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005248614,"about_ca_topic_score_gemma":0.007464529,"domain_scores_codex":[0.9990181,0.0001319675,0.0003186247,0.0002701766,0.0001742695,0.00008702527],"domain_scores_gemma":[0.9964893,0.001243734,0.0008710281,0.0006707037,0.0005105911,0.0002148276],"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":[0.0009433412,0.00004171549,0.02203272,0.007669724,0.0004511304,0.0005336039,0.00007005144,0.0007461205,0.0004102203,0.003154874,0.9011682,0.06277831],"study_design_scores_gemma":[0.0005875803,0.00007449088,0.04863514,0.006140624,0.0003526736,0.003089737,0.0001725844,0.0006411372,0.0004887247,0.006360597,0.9333669,0.00008983576],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001812074,0.002371215,0.0007562647,0.0002748136,0.000176783,0.0001132128,0.9843814,0.0003466962,0.009767511],"genre_scores_gemma":[0.00848243,0.002870796,0.001757773,0.000581305,0.0001612089,0.0004023914,0.982308,0.0001454767,0.003290544],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07288295,"threshold_uncertainty_score":0.2438177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01901686585826841,"score_gpt":0.4441782738365333,"score_spread":0.4251614079782649,"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."}}