{"id":"W2791219751","doi":"10.1109/lra.2018.2809512","title":"Free Head Movement Eye Gaze Contingent Ultrasound Interfaces for the da Vinci Surgical System","year":2018,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gaze; Modality (human–computer interaction); Computer vision; Eye tracking; Eye movement; Computer science; Artificial intelligence; Eye tracking on the ISS; Pupil; Psychology","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":[0.0005118779,0.000429178,0.0002357347,0.0002695632,0.0001851975,0.0003600416,0.0004843666,0.0005278043,0.005644178],"category_scores_gemma":[0.002018873,0.0001746497,0.0002199362,0.0001284213,0.000144275,0.000410219,0.0005132126,0.0003019702,0.0008345132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000212738,"about_ca_system_score_gemma":0.0002137249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000546099,"about_ca_topic_score_gemma":0.0008629585,"domain_scores_codex":[0.9996507,0.00009452378,0.00002938185,0.00005913009,0.0001376754,0.00002855902],"domain_scores_gemma":[0.9993389,0.0002913706,0.00007329973,0.0000789555,0.0001829615,0.00003444136],"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":[0.001646638,0.0002066628,0.002298225,0.0004825756,0.00006558107,0.000530582,0.0008700339,0.001979472,0.7232333,0.002272162,0.004163978,0.2622508],"study_design_scores_gemma":[0.0005991208,0.005818176,0.08131932,0.0002687417,0.000418144,0.006811818,0.0003723149,0.1738033,0.6520172,0.00260199,0.07560175,0.0003681087],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3666507,0.001366037,0.6196227,0.0003321485,0.0003408623,0.0004537988,0.0003960622,0.003962488,0.006875162],"genre_scores_gemma":[0.8742918,0.0004169696,0.117339,0.0003106416,0.00005637718,0.0003800514,0.0002660395,0.0001932082,0.006745907],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005644178,"threshold_uncertainty_score":0.01888162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01946166577728276,"score_gpt":0.2657788449880423,"score_spread":0.2463171792107596,"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."}}