{"id":"W4385967155","doi":"10.2196/48780","title":"Anki Tagger: A Generative AI Tool for Aligning Third-Party Resources to Preclinical Curriculum","year":2023,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Topic Modeling","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Curriculum; Generative grammar; Computer science; Artificial intelligence; Natural language processing; Psychology; Pedagogy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00105368,0.0001240532,0.0001789352,0.0001305853,0.0001615132,0.0001363004,0.0006957399,0.0001486251,0.00004196847],"category_scores_gemma":[0.001900399,0.0001068769,0.00007831231,0.0005779944,0.00003380387,0.0002594208,0.0002311508,0.0002096086,0.000152261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005956851,"about_ca_system_score_gemma":0.0008517387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002868854,"about_ca_topic_score_gemma":0.00001027239,"domain_scores_codex":[0.9979863,0.0001100105,0.0004038053,0.0005521397,0.0006112869,0.0003364456],"domain_scores_gemma":[0.9987178,0.0002657411,0.00008062472,0.0004487957,0.0001665796,0.0003204711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001287627,0.0004705484,0.002510403,0.00007457446,0.00002512379,0.000004213837,0.01728809,0.0002345415,0.0002903953,0.03600674,0.6604037,0.2826788],"study_design_scores_gemma":[0.0006039033,0.0002330836,0.004752234,0.0002788018,0.00001235327,0.00001185472,0.0006914296,0.6578592,0.0005003625,0.01184295,0.3227655,0.0004483161],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4571926,0.00006815698,0.45584,0.08237175,0.0023401,0.001125222,0.0000027141,0.0005152776,0.0005441748],"genre_scores_gemma":[0.7795308,0.00002198022,0.1665111,0.04073659,0.005222394,0.004040338,0.00006680306,0.00004288341,0.003827117],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6576247,"threshold_uncertainty_score":0.4358313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02941360689439209,"score_gpt":0.3854807537735736,"score_spread":0.3560671468791815,"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."}}