{"id":"W2909975787","doi":"10.4018/ijicthd.2019010102","title":"Podcasts and English-Language Learning","year":2019,"lang":"en","type":"article","venue":"International Journal of Information Communication Technologies and Human Development","topic":"Radio, Podcasts, and Digital Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Affordance; Class (philosophy); English language; Computer science; Language acquisition; Pedagogy; Mathematics education; Psychology; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005371754,0.0000615432,0.0001007136,0.0002859098,0.0002092566,0.0002775437,0.0004360462,0.0000676817,0.0000412198],"category_scores_gemma":[0.0004460737,0.00005587742,0.00001667569,0.00006313164,0.000148752,0.001367051,0.0001702578,0.000200444,0.0000104015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009597065,"about_ca_system_score_gemma":0.00007768552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002311058,"about_ca_topic_score_gemma":0.00002722579,"domain_scores_codex":[0.9991236,0.00003093417,0.0003845107,0.00004001447,0.000333546,0.00008740814],"domain_scores_gemma":[0.9989722,0.00008911167,0.0003891826,0.0000883114,0.0004276487,0.00003357584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002129628,0.00003025259,0.01776746,0.00001388609,0.00006436786,0.000001317699,0.1185443,0.0000136096,0.00003657717,0.08308682,0.0004445776,0.7799755],"study_design_scores_gemma":[0.001375945,0.0001818734,0.0245154,0.0002539872,0.000007470466,0.00003369365,0.3026563,0.00005018786,0.0007006206,0.003256967,0.6667038,0.0002636904],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.971288,0.0004246805,0.0001051321,0.001021114,0.0001779779,0.00009217318,6.701601e-7,0.00008596423,0.02680434],"genre_scores_gemma":[0.996558,0.001083686,0.00203732,0.00005761011,0.00002850805,0.000002806279,0.000009955992,0.00000241189,0.0002197654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7797118,"threshold_uncertainty_score":0.267636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01074113822571655,"score_gpt":0.2786863880822149,"score_spread":0.2679452498564983,"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."}}