{"id":"W2919671320","doi":"10.1016/j.echo.2018.12.001","title":"Optimal Technique for Measurement of Linear Left Ventricular Dimensions","year":2019,"lang":"en","type":"article","venue":"Journal of the American Society of Echocardiography","topic":"Cardiovascular Function and Risk Factors","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University; McGill University; Jewish General Hospital","funders":"National Heart, Lung, and Blood Institute","keywords":"Medicine; Ventricle; Parasternal line; Cardiology; Magnetic resonance imaging; Cardiomyopathy; Apex (geometry); Ellipsoid; Nuclear medicine; Internal medicine; Anatomy; Radiology; Heart failure; Physics","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":[0.00965908,0.0009499562,0.001637539,0.004093476,0.0009734176,0.001796159,0.001051432,0.002012502,0.004252589],"category_scores_gemma":[0.01936786,0.001696304,0.0009963111,0.001551101,0.001222259,0.00280894,0.002186208,0.003536666,0.002105777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003937437,"about_ca_system_score_gemma":0.001804877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008864103,"about_ca_topic_score_gemma":0.001733486,"domain_scores_codex":[0.9928927,0.002784951,0.0008918495,0.001379587,0.001639483,0.0004114544],"domain_scores_gemma":[0.9873928,0.006590655,0.0006434729,0.002570314,0.002347794,0.0004549406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00279671,0.000335734,0.03904375,0.001049301,0.0002691536,0.001276959,0.001580328,0.002365222,0.2266755,0.008218968,0.008064819,0.7083235],"study_design_scores_gemma":[0.001489,0.00453164,0.2765429,0.002292902,0.001965318,0.1014906,0.001679588,0.1339518,0.3592211,0.03735098,0.07807028,0.001414044],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03640151,0.003143002,0.9541263,0.0007270799,0.000340153,0.000239876,0.0002344464,0.001687229,0.003100458],"genre_scores_gemma":[0.07556594,0.001049503,0.9212959,0.0002838947,0.0002430203,0.0003336186,0.00008544255,0.0005068968,0.0006356528],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00965908,"threshold_uncertainty_score":0.05108273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01421873870320499,"score_gpt":0.2538269278904836,"score_spread":0.2396081891872786,"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."}}