{"id":"W4404565349","doi":"10.1097/prs.0000000000011863","title":"Intraoperative Surgical Guidance for DIEP Flap Harvest Using Augmented Reality","year":2024,"lang":"en","type":"article","venue":"Plastic & Reconstructive Surgery","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"DIEP flap; Surgery; Augmented reality; Medicine; Computer science; Breast reconstruction; Human–computer interaction","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005961254,0.0002469224,0.0005871457,0.0002179935,0.0001508818,0.00008582894,0.00004052867,0.0001291797,0.0006539284],"category_scores_gemma":[0.00187623,0.0002052847,0.000313584,0.0004063326,0.0002802225,0.0002240081,0.00002529436,0.0002654554,0.00003251492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001957751,"about_ca_system_score_gemma":0.0003545803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002517223,"about_ca_topic_score_gemma":0.000008351926,"domain_scores_codex":[0.9981245,0.0001156254,0.0005838439,0.0005353359,0.0002438426,0.0003968722],"domain_scores_gemma":[0.9897392,0.009564876,0.00008554336,0.0001531291,0.0002183938,0.0002388075],"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":[0.008218028,0.0006936797,0.3162249,0.002497928,0.003650995,0.003483508,0.001582042,0.001774285,0.003212331,0.0269525,0.002465931,0.6292439],"study_design_scores_gemma":[0.01211114,0.0006103812,0.1871547,0.009081485,0.001497838,0.004471167,0.001989974,0.630069,0.009178475,0.003860777,0.137396,0.002579069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9791822,0.0004871524,0.01270299,0.000192547,0.002672782,0.0004559893,0.0001616782,0.0002481437,0.003896459],"genre_scores_gemma":[0.9977408,0.00002009889,0.001236057,0.00005581915,0.0005730143,0.00004392201,0.00009593456,0.00003654545,0.0001977761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6282947,"threshold_uncertainty_score":0.8371266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07652625585240017,"score_gpt":0.3409407902952268,"score_spread":0.2644145344428267,"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."}}