{"id":"W2178624680","doi":"","title":"Fuzzy classification: towards evaluating performance on a surgical simulator.","year":2005,"lang":"en","type":"article","venue":"PubMed","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Surrey Memorial Hospital","funders":"","keywords":"Computer science; Fuzzy logic; Classifier (UML); Artificial intelligence; Machine learning; Simulation; Task (project management); Human–computer interaction; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006183002,0.0001145505,0.00018712,0.00007286107,0.00008954159,0.0000224655,0.00005690005,0.00008034915,0.0002697062],"category_scores_gemma":[0.0002228368,0.00009131855,0.00008754935,0.0002171535,0.00003806353,0.00008425614,0.00001565553,0.0001952114,0.0001692205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001129661,"about_ca_system_score_gemma":0.00003762917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001009717,"about_ca_topic_score_gemma":3.335702e-7,"domain_scores_codex":[0.998661,0.00004131637,0.0002687413,0.000243088,0.00047389,0.0003120051],"domain_scores_gemma":[0.9992489,0.0001642875,0.00005962017,0.0002097167,0.00008319248,0.0002342859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003007937,0.00007639285,0.01042275,0.00001152315,0.00001889448,0.000007763201,0.00005994537,0.002657116,0.00000221431,0.0007317141,0.00003384911,0.9856771],"study_design_scores_gemma":[0.004301257,0.00007675977,0.7999969,0.00001886,0.00002881736,0.00001972516,0.00002486017,0.07158183,0.0001175366,0.00002061822,0.1236945,0.0001184052],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7899383,0.00006095857,0.000004844328,0.002089343,0.00009197983,0.0004002343,8.030586e-7,0.0001237895,0.2072897],"genre_scores_gemma":[0.9961239,0.00001341933,0.000140272,0.0007666887,0.0008172487,0.0002119923,0.00001324181,0.00001605853,0.00189721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9855586,"threshold_uncertainty_score":0.3723862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1449413691681494,"score_gpt":0.3524750910057999,"score_spread":0.2075337218376505,"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."}}