{"id":"W1975398391","doi":"10.1080/01421590802108331","title":"AMEE Guide 32: e-Learning in medical education Part 1: Learning, teaching and assessment","year":2008,"lang":"en","type":"article","venue":"Medical Teacher","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":661,"is_retracted":false,"has_abstract":true,"ca_institutions":"NOSM University","funders":"","keywords":"Set (abstract data type); Creativity; Health care; Mainstream; Serendipity; Resource (disambiguation); Computer science; E learning; Psychology; Engineering ethics; Medical education; Knowledge management; Educational technology; Mathematics education; Medicine; Engineering; Political science","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":["metaresearch","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.008806784,0.0001292309,0.0002467906,0.0001250318,0.001013954,0.00003154366,0.000260823,0.0004493179,0.005036732],"category_scores_gemma":[0.08403338,0.0001299021,0.00003779061,0.0002653353,0.000585511,0.0001708682,0.00006811557,0.002928847,0.00004425074],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005327371,"about_ca_system_score_gemma":0.006743947,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01430011,"about_ca_topic_score_gemma":0.00207685,"domain_scores_codex":[0.9937925,0.002934798,0.0004858253,0.0003433071,0.00193785,0.0005056962],"domain_scores_gemma":[0.9975924,0.001207799,0.0001422418,0.0001127751,0.00006517106,0.0008795524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002316914,0.0002389082,0.6453535,0.00001328674,0.000004540847,0.00001127938,0.03961354,6.085552e-7,3.62119e-7,0.001939637,0.008934347,0.3038876],"study_design_scores_gemma":[0.0002929901,0.00004139177,0.10306,0.0001661413,0.000005738231,0.000009396564,0.01398755,0.0007404132,2.113789e-7,0.0001898313,0.8813598,0.0001465757],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8440095,0.000439255,0.00007606143,0.04190844,0.002664065,0.0004429784,6.007983e-8,0.0001625932,0.1102971],"genre_scores_gemma":[0.9810237,0.001763689,0.001066683,0.001613173,0.004590011,0.0005200619,0.0000170129,0.00003158152,0.009374036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8724254,"threshold_uncertainty_score":0.9993714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07933230968797282,"score_gpt":0.4595180280505878,"score_spread":0.3801857183626149,"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."}}