{"id":"W2979313613","doi":"10.29173/iasl7194","title":"Evaluation of Digital Contents in Education: Examples of English and Health Education Applications in Japan","year":2016,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"Open Education and E-Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quality (philosophy); Order (exchange); Computer science; Digital learning; Government (linguistics); Mathematics education; Multimedia; Unit (ring theory); Medical education; Psychology; Medicine; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003410636,0.0003083916,0.0002191144,0.002379916,0.001043431,0.001932676,0.0003701324,0.0004427306,0.001852894],"category_scores_gemma":[0.008360308,0.0001071816,0.0002983049,0.003103713,0.0006671593,0.001220173,0.001185493,0.0002364474,0.0004276483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001610934,"about_ca_system_score_gemma":0.001088976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006718183,"about_ca_topic_score_gemma":0.01205818,"domain_scores_codex":[0.9971157,0.001230574,0.0002561453,0.0001755361,0.001029361,0.0001925717],"domain_scores_gemma":[0.9937814,0.00213013,0.0003518414,0.0003766824,0.002846938,0.00051305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006077638,0.0009373376,0.08203463,0.002140676,0.00007186463,0.002538052,0.03379166,0.001465674,0.01614041,0.008043163,0.01048358,0.8417451],"study_design_scores_gemma":[0.0001585097,0.002361561,0.5130603,0.001811387,0.000609936,0.004154043,0.05546249,0.01287591,0.05420946,0.006669473,0.3483895,0.0002375044],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8850728,0.008252822,0.01412285,0.001313839,0.0001328968,0.0005184499,0.0001881703,0.0002295881,0.0901686],"genre_scores_gemma":[0.9604883,0.003620717,0.0231777,0.0001548923,0.00004402227,0.0001212265,0.0002121208,0.00008310699,0.01209792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006718183,"threshold_uncertainty_score":0.01803738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06315726146896863,"score_gpt":0.3341786211674239,"score_spread":0.2710213596984552,"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."}}