{"id":"W2382433494","doi":"","title":"The Interactive Learning Platform WebCT with MSN-based Training in English Listening and Speaking","year":2009,"lang":"en","type":"article","venue":"Computer Knowledge and Technology","topic":"Higher Education and Teaching Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Active listening; Computer science; Multimedia; Virtual learning environment; Human–computer interaction; Psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.0005149732,0.0001492994,0.0001904926,0.0003535088,0.0003155768,0.0002050462,0.000387151,0.00009518613,6.372173e-7],"category_scores_gemma":[0.0001084851,0.0001072921,0.00001646849,0.0005833944,0.0001188107,0.0002351521,0.0001427492,0.0006115204,0.000001483983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003355771,"about_ca_system_score_gemma":0.00008684912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003553442,"about_ca_topic_score_gemma":0.00004618479,"domain_scores_codex":[0.9990114,0.00009901918,0.0001794564,0.0003655622,0.00006106398,0.000283487],"domain_scores_gemma":[0.9989592,0.0005822703,0.00008361987,0.0002362963,0.00008748586,0.00005111436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006442926,0.00002703612,0.003483855,0.000004689466,0.00000791891,0.00001082328,0.01987412,0.0000339566,0.0000260025,0.03550434,0.00001455455,0.9410062],"study_design_scores_gemma":[0.003336569,0.002048972,0.03953038,0.000787433,0.00002401336,0.0002500254,0.005106123,0.752829,0.001300955,0.01990792,0.1737872,0.001091324],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2901046,0.001127502,0.700518,0.002575901,0.000536913,0.0001741396,1.010842e-7,0.0006319301,0.004330947],"genre_scores_gemma":[0.9241066,0.00001219472,0.07562833,0.0001013518,0.00008926123,0.000007339519,5.154381e-7,0.000006662643,0.0000477684],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9399149,"threshold_uncertainty_score":0.4375243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01640945271700565,"score_gpt":0.2911556287754302,"score_spread":0.2747461760584245,"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."}}