{"id":"W2590914037","doi":"10.1017/s0022215116005211","title":"An ear microsurgery trainer for low-resource settings","year":2016,"lang":"en","type":"article","venue":"The Journal of Laryngology & Otology","topic":"Global Health and Surgery","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Trainer; Microsurgery; Computer science; Resource (disambiguation); Content (measure theory); Action (physics); Multimedia; Medicine; Surgery; Mathematics; Operating system","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":[0.0009257857,0.0006778293,0.0006243355,0.0006430621,0.0008849592,0.0004625379,0.0008260699,0.0004762282,0.0417533],"category_scores_gemma":[0.001016227,0.0003439442,0.0006403445,0.0003657276,0.0003728475,0.0004701945,0.00113963,0.0008289772,0.01200253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003424837,"about_ca_system_score_gemma":0.0009775725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00098609,"about_ca_topic_score_gemma":0.003432234,"domain_scores_codex":[0.9995141,0.00005092316,0.00003496525,0.0001357376,0.0001656329,0.0000987386],"domain_scores_gemma":[0.9995442,0.0001106043,0.00005341705,0.0000818413,0.00008951937,0.0001203999],"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":[0.0008930484,0.0005071401,0.01073487,0.000509234,0.00005319518,0.001785005,0.0003672397,0.0005629291,0.8287245,0.0004741039,0.006819118,0.1485696],"study_design_scores_gemma":[0.0002928805,0.008064145,0.2094144,0.0003066626,0.0004393556,0.01972518,0.001519828,0.01244602,0.5719454,0.001162709,0.1743978,0.0002855034],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7064404,0.001350665,0.2461569,0.001065104,0.0009936667,0.003475965,0.003916394,0.00885798,0.02774297],"genre_scores_gemma":[0.6050867,0.001558733,0.2825021,0.0009387598,0.0001736802,0.005704285,0.004195362,0.001183077,0.09865726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0417533,"threshold_uncertainty_score":0.1396787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01140351815674102,"score_gpt":0.2932102656902273,"score_spread":0.2818067475334863,"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."}}