{"id":"W2233370095","doi":"","title":"Creating a computerized multimedia Chinese language lesson from authentic web text, using the KEY 4.0 software (for both PC and Mac)","year":2002,"lang":"en","type":"article","venue":"E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education","topic":"Higher Education and Teaching Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Multimedia; Key (lock); World Wide Web; Computer science; Software; The Internet; Computer software; Software engineering; Programming language; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003109278,0.001023546,0.0003385447,0.0007778936,0.0005298687,0.0007806073,0.001155449,0.0006861322,0.03957158],"category_scores_gemma":[0.001649061,0.0001945482,0.0003600853,0.0004235765,0.0004112492,0.0009326946,0.000927392,0.0005507609,0.005837578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004262459,"about_ca_system_score_gemma":0.0008279079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001640601,"about_ca_topic_score_gemma":0.002972909,"domain_scores_codex":[0.9998407,0.00003086787,0.00001148338,0.0000516562,0.00004216406,0.00002312247],"domain_scores_gemma":[0.9995093,0.0002478704,0.00002248569,0.00006212518,0.00007009586,0.00008806281],"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":[0.0006259279,0.001994501,0.003333703,0.001546616,0.00003336334,0.00173715,0.006577652,0.005964457,0.1468291,0.01123788,0.06025735,0.7598624],"study_design_scores_gemma":[0.00156107,0.005126394,0.02937392,0.0005779893,0.0002354367,0.004171391,0.006954344,0.07428024,0.3350199,0.01610532,0.526233,0.0003609346],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.4436079,0.0002940321,0.3346431,0.001136603,0.0006599694,0.006717144,0.00346254,0.02278339,0.1866952],"genre_scores_gemma":[0.3631877,0.0002627791,0.5452217,0.0004459321,0.00007229739,0.001766777,0.002326044,0.001784589,0.08493224],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03957158,"threshold_uncertainty_score":0.1323801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08035693616790186,"score_gpt":0.3321116688943283,"score_spread":0.2517547327264265,"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."}}