{"id":"W2592660893","doi":"10.22489/cinc.2016.055-149","title":"The Pressure Gradient across the Endocardium","year":2016,"lang":"en","type":"article","venue":"Computing in cardiology","topic":"Cardiovascular Function and Risk Factors","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Endocardium; Pressure gradient; Computer science; Cardiology; Physics; Mechanics; Medicine","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":[0.0006316184,0.0005261577,0.0005171657,0.0009123128,0.0003183887,0.001568081,0.0009058478,0.0007638246,0.002869226],"category_scores_gemma":[0.00219367,0.0003119989,0.0004297827,0.0005475445,0.001228393,0.00216904,0.001031045,0.0009715696,0.0009275374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003171657,"about_ca_system_score_gemma":0.0004911707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004311639,"about_ca_topic_score_gemma":0.0001740839,"domain_scores_codex":[0.9995272,0.00009675173,0.00003419086,0.0001352517,0.0001671466,0.00003944008],"domain_scores_gemma":[0.9993784,0.0003115637,0.0000925973,0.00006381398,0.0001174926,0.00003611288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001028693,0.00008267634,0.002179503,0.0009519746,0.0001230906,0.001313344,0.000584376,0.07714259,0.1250264,0.6725958,0.005240219,0.1146572],"study_design_scores_gemma":[0.00007772855,0.0004783018,0.01147945,0.0001849564,0.0001166541,0.005401812,0.0002782666,0.5448174,0.04238887,0.3353117,0.05919111,0.0002737843],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05016352,0.006461158,0.9135038,0.002019439,0.00101217,0.00008212313,0.0005274114,0.000785064,0.02544527],"genre_scores_gemma":[0.8920466,0.006563333,0.07238296,0.000790344,0.000894041,0.0001771314,0.0002712058,0.0003780602,0.02649635],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002869226,"threshold_uncertainty_score":0.009598494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01493191383811135,"score_gpt":0.2785314211637943,"score_spread":0.2635995073256829,"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."}}