{"id":"W1968210089","doi":"10.1007/s10459-011-9300-9","title":"Podcasting in medical education: can we turn this toy into an effective learning tool?","year":2011,"lang":"en","type":"article","venue":"Advances in Health Sciences Education","topic":"Innovations in Educational Methods","field":"Social Sciences","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Health Sciences Centre; University of Calgary","funders":"","keywords":"Limiting; Emerging technologies; Medical education; Engineering ethics; Computer science; Medicine; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0104444,0.0001594728,0.0002234402,0.0007864636,0.001256184,0.00007559361,0.0006935752,0.000131514,0.0004598529],"category_scores_gemma":[0.008271223,0.000166159,0.00002519396,0.003902869,0.0008305812,0.001895603,0.0000474,0.0005351538,0.00001350312],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001340853,"about_ca_system_score_gemma":0.01722631,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02587413,"about_ca_topic_score_gemma":0.02970318,"domain_scores_codex":[0.9955753,0.001609947,0.000743921,0.0005983731,0.0008791583,0.0005932629],"domain_scores_gemma":[0.9980074,0.0007495618,0.0004401013,0.0002078828,0.000352306,0.0002427332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000005474912,0.0003771863,0.1171362,0.00005497693,6.625809e-7,2.060377e-7,0.09360084,0.00006730024,0.000001852388,0.1196319,0.00005668224,0.6690668],"study_design_scores_gemma":[0.0003478492,0.0006219996,0.1682585,0.001885479,0.000005259593,0.00001787418,0.2630928,0.001210354,0.00006961086,0.3908886,0.1727808,0.0008208198],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8288962,0.009081857,0.0008905641,0.03623349,0.01783574,0.002090442,0.000001374005,0.0001607189,0.1048096],"genre_scores_gemma":[0.8926996,0.001730901,0.1012026,0.002353554,0.00102416,0.0005371258,0.00001094024,0.00001316858,0.0004280218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6682459,"threshold_uncertainty_score":0.9902024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0441304553435004,"score_gpt":0.493051398578435,"score_spread":0.4489209432349346,"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."}}