{"id":"W1817978889","doi":"10.1109/scamc.1978.679961","title":"Computer Support For Muscular Subaortic Stenosis Research","year":2005,"lang":"en","type":"article","venue":"","topic":"Cardiac Valve Diseases and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital","funders":"","keywords":"Computer science; Data collection; Minicomputer; Data management; Process (computing); Generator (circuit theory); Database; Data science; Information retrieval; Operating system","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":[0.01120817,0.0007311734,0.00108224,0.003032352,0.0006564073,0.002085566,0.001975142,0.0005763617,0.04570207],"category_scores_gemma":[0.02901145,0.0005690416,0.000557573,0.002825972,0.0004073241,0.002350311,0.002032628,0.001114879,0.02174261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006114769,"about_ca_system_score_gemma":0.001601021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001086092,"about_ca_topic_score_gemma":0.0008846784,"domain_scores_codex":[0.9951403,0.002224103,0.000838636,0.0006818241,0.0009119104,0.0002032554],"domain_scores_gemma":[0.9617311,0.02281431,0.00114686,0.00681317,0.005078259,0.002416294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002769686,0.0004255081,0.007640605,0.0007200459,0.0001139079,0.0009701668,0.001048378,0.0009770134,0.0195219,0.007194063,0.1966869,0.7619318],"study_design_scores_gemma":[0.004504668,0.002528023,0.03495539,0.001105854,0.0005225508,0.005240588,0.0006063817,0.04712046,0.0466444,0.02043656,0.8359379,0.0003971552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07958654,0.005512403,0.626158,0.006819488,0.001413623,0.007573918,0.01505196,0.1891036,0.06878045],"genre_scores_gemma":[0.2405796,0.004339214,0.6608264,0.002212368,0.003021409,0.00922711,0.01988269,0.007299412,0.05261187],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04570207,"threshold_uncertainty_score":0.1528887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05864330590540251,"score_gpt":0.4396446404890429,"score_spread":0.3810013345836404,"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."}}