{"id":"W2995810409","doi":"10.29007/tpbf","title":"Depth Camera Augmented Fluoroscopy with Video Overlay","year":2019,"lang":"en","type":"article","venue":"EPiC series in health sciences","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Overlay; Fluoroscopy; Computer vision; Computer science; Artificial intelligence; Video camera; Computer graphics (images); Medicine; Surgery","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":[0.0005800909,0.0005637954,0.0004399677,0.0007184624,0.0001860538,0.0008672415,0.0008076937,0.0006733692,0.006097328],"category_scores_gemma":[0.003780796,0.0003482404,0.0004338727,0.0004082367,0.0002732432,0.001014428,0.001395919,0.000584199,0.0006476411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004146328,"about_ca_system_score_gemma":0.0008697066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00357029,"about_ca_topic_score_gemma":0.003820034,"domain_scores_codex":[0.9990701,0.0001490107,0.00005907383,0.0001028186,0.0005293458,0.0000896692],"domain_scores_gemma":[0.9984326,0.0006565215,0.0001461808,0.0002086398,0.0004635008,0.00009263396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001986136,0.000434504,0.00471658,0.001007188,0.0001100725,0.001050748,0.0006532695,0.03660516,0.2816598,0.003481199,0.009118938,0.6591764],"study_design_scores_gemma":[0.000657809,0.006627512,0.03463086,0.0005953446,0.000293587,0.01329973,0.0003962077,0.4621696,0.3520012,0.003943203,0.1245458,0.0008391406],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1771436,0.001917723,0.797692,0.000517344,0.0003402072,0.0006734336,0.0008329978,0.006696547,0.01418614],"genre_scores_gemma":[0.6013448,0.001072737,0.3909372,0.0002839675,0.0001062327,0.0002247685,0.0004336459,0.0002796639,0.005317091],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006097328,"threshold_uncertainty_score":0.02039754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03242647111111842,"score_gpt":0.3528805341244737,"score_spread":0.3204540630133553,"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."}}