{"id":"W4406741829","doi":"10.1016/j.jtcvs.2024.12.034","title":"Mixed reality for preoperative planning and intraoperative assistance of surgical correction of complex congenital heart defects","year":2025,"lang":"en","type":"article","venue":"Journal of Thoracic and Cardiovascular Surgery","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children","funders":"Fundación Pública Andaluza para la Gestión de la Investigación en Salud de Sevilla; Hospital for Sick Children; Medtronic","keywords":"Medicine; Surgical planning; Surgery; Surgical procedures","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":[0.002065195,0.0001051167,0.000675057,0.0001466798,0.0001083147,0.00003885643,0.0001154689,0.00006537478,7.25177e-7],"category_scores_gemma":[0.0001529826,0.00008951707,0.0004469791,0.0002957273,0.0001551989,0.000243051,0.00006724295,0.000129601,4.064684e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002775395,"about_ca_system_score_gemma":0.0001574513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000018579,"about_ca_topic_score_gemma":0.000003735436,"domain_scores_codex":[0.9985523,0.0003656688,0.0005242556,0.0001890127,0.0002539487,0.0001147812],"domain_scores_gemma":[0.9981162,0.0008512221,0.0002577859,0.0002335956,0.0004794763,0.00006172735],"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":[0.003535873,0.001442712,0.1406537,0.003552444,0.02451423,0.0002072288,0.008825928,0.03731414,0.01333397,0.02692601,0.03399428,0.7056994],"study_design_scores_gemma":[0.003678308,0.0009276307,0.6587935,0.002976428,0.003003727,0.002295092,0.004582422,0.09808607,0.1866988,0.004183072,0.03347442,0.00130051],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3529716,0.006015867,0.6401833,0.000204751,0.0002511088,0.0001944478,0.00001234922,0.000007395524,0.0001592003],"genre_scores_gemma":[0.9967533,0.0002661746,0.002890949,0.00001723629,0.00003491848,0.00001121872,0.000002942548,0.000003840907,0.00001937787],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.704399,"threshold_uncertainty_score":0.36504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04364650210593594,"score_gpt":0.3190266810172653,"score_spread":0.2753801789113293,"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."}}