{"id":"W2732029736","doi":"10.1145/3059009.3059027","title":"Computing for Medicine","year":2017,"lang":"en","type":"article","venue":"","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Context (archaeology); Computer science; Medical education; Computational thinking; Multimedia; Mathematics education; Psychology; Medicine; Artificial intelligence","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":[0.001194942,0.000557951,0.0002980221,0.001064493,0.001501137,0.004467635,0.0009340735,0.001986248,0.1198325],"category_scores_gemma":[0.00719821,0.0001802394,0.0004409487,0.0007802723,0.001722133,0.003219805,0.005334917,0.002893564,0.03904117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009853697,"about_ca_system_score_gemma":0.002389576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005890086,"about_ca_topic_score_gemma":0.001242601,"domain_scores_codex":[0.9987412,0.000313966,0.00007452071,0.0001849242,0.0005453448,0.0001400879],"domain_scores_gemma":[0.9962056,0.0009136064,0.000198885,0.0005394497,0.0005779244,0.001564508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005203842,0.0000651637,0.001236766,0.0005703283,0.00001909617,0.00058463,0.0009180025,0.0002392216,0.00207571,0.07094663,0.4902097,0.4330826],"study_design_scores_gemma":[0.000005492583,0.00002815051,0.0004257901,0.0002219979,0.000003940762,0.001365236,0.0001641257,0.00008254908,0.0001949162,0.01290224,0.9845962,0.000009384545],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.007840651,0.08242416,0.05095248,0.188713,0.03230277,0.0002961656,0.0008695706,0.002814648,0.6337866],"genre_scores_gemma":[0.1323301,0.09571385,0.09010967,0.1197731,0.02500805,0.0004489315,0.001743986,0.001606492,0.5332659],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1198325,"threshold_uncertainty_score":0.4008796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02191049853575758,"score_gpt":0.2749974069228528,"score_spread":0.2530869083870952,"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."}}