{"id":"W3017253860","doi":"10.1007/s11548-020-02141-y","title":"Cardiac point-of-care to cart-based ultrasound translation using constrained CycleGAN","year":2020,"lang":"en","type":"article","venue":"International Journal of Computer Assisted Radiology and Surgery","topic":"Cardiovascular Function and Risk Factors","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"Vancouver General Hospital; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Cart; Computer science; Segmentation; Artificial intelligence; Deep learning; Echo (communications protocol); Image translation; Translation (biology); Computer vision; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002678788,0.0001047644,0.0005389787,0.000266837,0.00002847829,0.00001511614,0.00005893478,0.00009271973,0.00002584847],"category_scores_gemma":[0.0001047848,0.0000872711,0.0005469706,0.0001130078,0.00008371645,0.00006708815,0.00000810421,0.0001712302,8.258543e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004250085,"about_ca_system_score_gemma":0.0002076609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005218545,"about_ca_topic_score_gemma":4.756474e-7,"domain_scores_codex":[0.9988905,0.0001546808,0.0004748839,0.0001248819,0.000262178,0.00009287848],"domain_scores_gemma":[0.9986017,0.000511604,0.0001885202,0.00006313908,0.0004572738,0.0001776991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004273988,0.0001627212,0.7633687,0.000189143,0.006912629,0.0008707983,0.002893274,0.009094913,0.05013559,0.0000900638,0.003644049,0.1583641],"study_design_scores_gemma":[0.005548952,0.001011506,0.9451434,0.00066672,0.001169695,0.007863258,0.0009253518,0.007204965,0.006995593,0.00001638991,0.02301989,0.0004342937],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8871652,0.0008113508,0.1073635,0.002538031,0.001944278,0.00009177892,0.00001869122,0.0000133329,0.00005374719],"genre_scores_gemma":[0.9924477,0.00006646145,0.005613338,0.001068168,0.000763546,4.345254e-7,0.00003028406,0.000009017896,0.000001042722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1817747,"threshold_uncertainty_score":0.3558812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03015808527696146,"score_gpt":0.2742909717232664,"score_spread":0.244132886446305,"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."}}