{"id":"W2479676305","doi":"10.1115/1.4033801","title":"An Assistant Robot System for Sinus Surgery1","year":2016,"lang":"en","type":"article","venue":"Journal of Medical Devices","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Endoscope; Workspace; Robot; Computer vision; Kinematics; Artificial intelligence; Computer science; Surgery; Engineering; Simulation; Medicine; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003316022,0.0007424997,0.0004836771,0.0004984594,0.0004027483,0.0005951991,0.0009724767,0.0007910741,0.01540226],"category_scores_gemma":[0.0004588145,0.0001974375,0.0003717313,0.0002652604,0.0001958623,0.0004750184,0.0006487318,0.0004608736,0.004751471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001466865,"about_ca_system_score_gemma":0.0005407548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004722026,"about_ca_topic_score_gemma":0.0004769498,"domain_scores_codex":[0.9996845,0.00004465853,0.00002329745,0.00007210371,0.0001470732,0.0000285363],"domain_scores_gemma":[0.999724,0.00005174631,0.00003101922,0.00004388119,0.0001122334,0.00003719385],"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":[0.0008970655,0.0003016893,0.001894532,0.0008667919,0.0000610124,0.0008569885,0.0002376082,0.004912465,0.297051,0.003647785,0.02037607,0.668897],"study_design_scores_gemma":[0.001128167,0.01420759,0.01523826,0.0002710069,0.0004269005,0.01360511,0.0001903723,0.2560581,0.1794995,0.004072346,0.5149352,0.0003676557],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06875231,0.002711396,0.8705968,0.0004204696,0.001386557,0.0009254263,0.0008582562,0.02499802,0.02935074],"genre_scores_gemma":[0.5033383,0.001602585,0.4386123,0.0006333475,0.0007374076,0.0009132554,0.00170123,0.0003656655,0.05209581],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01540226,"threshold_uncertainty_score":0.05152571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01664444024811716,"score_gpt":0.2728501768084257,"score_spread":0.2562057365603085,"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."}}