{"id":"W7006357947","doi":"","title":"Tips for using mobile audience response systems in medical education","year":2016,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Innovative Teaching Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interactivity; Audience response; Mobile device; Mobile technology; Target audience","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.02654103,0.0001784176,0.0005081816,0.0008502232,0.0005249033,0.000565668,0.002381017,0.0001755772,0.002124035],"category_scores_gemma":[0.0161787,0.0001376499,0.00008901855,0.00141565,0.0004180823,0.002177829,0.0003474759,0.0002767583,0.000005960497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006925918,"about_ca_system_score_gemma":0.002621388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004935069,"about_ca_topic_score_gemma":0.0002942712,"domain_scores_codex":[0.9936412,0.003575934,0.0008507147,0.0003842237,0.00107952,0.0004684224],"domain_scores_gemma":[0.9950229,0.003006863,0.0007900378,0.0003020728,0.0006335752,0.0002445415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001651234,0.0008528581,0.494191,0.000150028,0.000101231,0.00002346509,0.007329967,0.00006899513,0.2226025,0.01841747,0.02754153,0.2270697],"study_design_scores_gemma":[0.00257243,0.00007701887,0.627318,0.008102844,0.00008764787,0.00004636949,0.007358591,0.0006597291,0.01453909,0.04462742,0.2929261,0.001684794],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9722311,0.003509649,0.01722867,0.0008030584,0.002059063,0.001127931,0.00001481472,0.00003294542,0.002992703],"genre_scores_gemma":[0.9947858,0.0007010451,0.002803458,0.0002164494,0.0004311923,0.0001905752,9.641706e-7,0.00003056478,0.0008398759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2653846,"threshold_uncertainty_score":0.9987882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.442636238827208,"score_gpt":0.6808816911648234,"score_spread":0.2382454523376154,"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."}}