{"id":"W2957716842","doi":"10.1016/j.carj.2019.03.007","title":"Developing the Evidence Base for M-Learning in Undergraduate Radiology Education: Identifying Learner Preferences for Mobile Apps","year":2019,"lang":"en","type":"article","venue":"Canadian Association of Radiologists Journal","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medicine; Presentation (obstetrics); Radiology; Medical education; Academic institution; Test (biology); Multimedia; Computer 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":[],"consensus_categories":[],"category_scores_codex":[0.005890927,0.0001326279,0.0003709969,0.0002962479,0.001169825,0.00002316277,0.0003377156,0.0003002302,0.00007780267],"category_scores_gemma":[0.004675921,0.0001070524,0.00009550376,0.0002999906,0.00004387628,0.0001661227,0.00001726846,0.0008675267,0.00003057746],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003240117,"about_ca_system_score_gemma":0.01260455,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003684948,"about_ca_topic_score_gemma":0.04124957,"domain_scores_codex":[0.9967813,0.001013019,0.0009782206,0.0002670831,0.000152174,0.0008082132],"domain_scores_gemma":[0.9925453,0.004912441,0.00134557,0.0001860092,0.0006972185,0.0003134296],"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":[0.00008425773,0.0000207593,0.8814939,0.0007045967,0.00004736399,3.644179e-7,0.001370267,0.001255586,0.00005261226,0.02625702,0.05096713,0.03774611],"study_design_scores_gemma":[0.002220513,0.0003698727,0.2436229,0.001192632,0.00005010075,0.00002592131,0.007906221,0.00124066,0.00001108953,0.0265546,0.7164719,0.0003335596],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7766482,0.01178082,0.03968991,0.1297082,0.01019025,0.02858777,0.0001593059,0.0001145649,0.003120926],"genre_scores_gemma":[0.977375,0.003093102,0.004359434,0.002959409,0.0006255197,0.006918409,0.0000638264,0.0000240928,0.004581192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6655048,"threshold_uncertainty_score":0.9929931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09746223181325123,"score_gpt":0.4317507057491457,"score_spread":0.3342884739358944,"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."}}