{"id":"W2120374623","doi":"10.1002/mrm.22664","title":"Functional MRI‐compatible laparoscopic surgery training simulator","year":2010,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Baycrest Hospital; St. Michael's Hospital","funders":"","keywords":"Laparoscopy; Computer science; Eye–hand coordination; Task (project management); Laparoscopic surgery; Physical medicine and rehabilitation; Simulation; Medicine; Artificial intelligence; Radiology","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":[0.0003288174,0.0005690226,0.0002205338,0.0002472406,0.0001388242,0.0001539384,0.0005567396,0.0004509202,0.004181007],"category_scores_gemma":[0.0006509725,0.0001735946,0.0002321437,0.00007285378,0.000243119,0.0002265598,0.0005828309,0.0004132446,0.0008443442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001134028,"about_ca_system_score_gemma":0.0004637016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000409075,"about_ca_topic_score_gemma":0.0005502635,"domain_scores_codex":[0.9998848,0.00003248377,0.000009712323,0.00002170919,0.00002932113,0.00002193675],"domain_scores_gemma":[0.9997095,0.00007938774,0.00002839959,0.00003846215,0.00005087463,0.00009335126],"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":[0.001622031,0.003246113,0.00334441,0.0002658374,0.00005448834,0.0008101139,0.0003328649,0.008139179,0.9437666,0.0007456972,0.001437453,0.03623531],"study_design_scores_gemma":[0.002845982,0.08976676,0.1417867,0.0001688882,0.0003530204,0.01620284,0.0007730597,0.1772111,0.5008929,0.004408334,0.06513747,0.0004530148],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9124519,0.00008675741,0.07983154,0.0003530497,0.0001054003,0.001100097,0.001093262,0.0004835605,0.004494375],"genre_scores_gemma":[0.935406,0.0001810993,0.05480685,0.000338122,0.00005299043,0.001357614,0.001092854,0.00006156236,0.006702974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004181007,"threshold_uncertainty_score":0.01398683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05812844068592798,"score_gpt":0.3094339178829045,"score_spread":0.2513054771969765,"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."}}