{"id":"W2753558111","doi":"10.1016/j.jcjd.2017.08.004","title":"Computer Simulation Model to Train Medical Personnel on Glucose Clamp Procedures","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Diabetes","topic":"Hyperglycemia and glycemic control in critically ill and hospitalized patients","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Montreal Clinical Research Institute; McGill University","funders":"Medtronic; Eli Lilly and Company","keywords":"Medicine; Clamp; Medical physics; Simulation; Mechanical engineering; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0004650452,0.0006432444,0.0006190225,0.0006013583,0.0004837737,0.0006466231,0.001180845,0.001671415,0.008768227],"category_scores_gemma":[0.002924958,0.0004671147,0.00051361,0.0004040479,0.0003016643,0.0004378391,0.0004930517,0.0008838286,0.0005530471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001156898,"about_ca_system_score_gemma":0.002556501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0659012,"about_ca_topic_score_gemma":0.02529234,"domain_scores_codex":[0.9997576,0.0001128727,0.00001244201,0.00003285588,0.00003886947,0.00004541941],"domain_scores_gemma":[0.9976999,0.001694253,0.00009318244,0.0000491573,0.0003271834,0.0001364086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007452023,0.0000880987,0.0007870737,0.00001045017,0.000007180096,0.00002657625,0.00001724372,0.9960449,0.000101677,0.0003860755,0.0002406073,0.002215568],"study_design_scores_gemma":[0.00002073055,0.0000254099,0.0001035965,0.000002599818,0.000003466456,0.00000342555,0.000009079918,0.9995311,0.00006414188,0.0001395878,0.00009479094,0.000002103362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6528119,0.0002623073,0.3091072,0.001465615,0.0002833648,0.0004779785,0.001287208,0.001570229,0.03273424],"genre_scores_gemma":[0.9716833,0.0001085755,0.02156753,0.0001014103,0.00001987472,0.0002904368,0.0004425535,0.00004065361,0.005745528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0659012,"threshold_uncertainty_score":0.1310352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02720225427960315,"score_gpt":0.2989934595043608,"score_spread":0.2717912052247577,"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."}}