{"id":"W3108814846","doi":"10.1109/tmrb.2020.3041897","title":"Development of a Steerable Miniature Instrument to Manage Internal Carotid Artery Injury in Endoscopic Transsphenoidal Surgery Simulation","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Robotics and Bionics","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Sinai Health System; Hospital for Sick Children; University of Toronto","funders":"Hospital for Sick Children; University of Toronto","keywords":"Internal carotid artery; Visualization; Simulation; Computer science; Biomedical engineering; Surgery; Medicine; Computer vision; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000445973,0.0004338167,0.000316704,0.0003155521,0.0001879556,0.0003836811,0.0007604035,0.0005981603,0.001477038],"category_scores_gemma":[0.0007057112,0.0002812908,0.0005146443,0.0001080209,0.0003014251,0.0003762544,0.0005555228,0.0002985798,0.0004050904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001674534,"about_ca_system_score_gemma":0.0007862336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006134596,"about_ca_topic_score_gemma":0.0005621213,"domain_scores_codex":[0.9997033,0.00004793692,0.00001969133,0.0000423221,0.0001545,0.00003222761],"domain_scores_gemma":[0.9997143,0.00006616843,0.00003773477,0.00006613052,0.00006930089,0.00004616655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004229474,0.0003966053,0.005446047,0.0006055975,0.00007813316,0.001332093,0.0004785853,0.299309,0.5162112,0.004215411,0.001588959,0.1699155],"study_design_scores_gemma":[0.000133361,0.004694283,0.006200903,0.00009661975,0.0001074965,0.002737492,0.000148296,0.7673732,0.1946555,0.00132103,0.02237393,0.0001577665],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2550226,0.000354237,0.7379243,0.0001587092,0.0001121717,0.0004669556,0.0001427263,0.001481449,0.004336897],"genre_scores_gemma":[0.7267087,0.0003719262,0.2697286,0.00004476528,0.00001249952,0.0003151088,0.0001341216,0.00005718297,0.002627273],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001477038,"threshold_uncertainty_score":0.004941165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01958241177816059,"score_gpt":0.2380884670265539,"score_spread":0.2185060552483933,"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."}}