{"id":"W437063635","doi":"","title":"イマージョン ランゲージ エジュケーション--日本においての英語教育モデル","year":2007,"lang":"ja","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009197741,0.0007591933,0.0006014087,0.0004248871,0.0011634,0.0001765826,0.0008073855,0.0007688552,0.0003185988],"category_scores_gemma":[0.0005345664,0.0008231176,0.0002530939,0.0008480607,0.001323121,0.001607597,0.0003487854,0.001366781,0.0005823408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005934618,"about_ca_system_score_gemma":0.0005300493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007847319,"about_ca_topic_score_gemma":0.0006158384,"domain_scores_codex":[0.9957442,0.00006014309,0.001216623,0.0009211554,0.0008886409,0.001169203],"domain_scores_gemma":[0.9974227,0.0003060605,0.0001575229,0.001422282,0.0003079562,0.0003834818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003331691,0.0003080897,0.00349784,0.0005838611,0.0005773604,0.004085295,0.0006084267,0.001694183,0.01349508,0.9575968,0.01539436,0.001825497],"study_design_scores_gemma":[0.00260265,0.0004776282,0.02152734,0.001707345,0.000538418,0.003292756,0.002950296,0.002181817,0.04847856,0.01111316,0.901762,0.003368045],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3097446,0.0355657,0.05211322,0.0008709279,0.04079709,0.001177707,0.003367435,0.003252779,0.5531105],"genre_scores_gemma":[0.9873469,0.0008383418,0.00599263,0.0001177335,0.002836894,0.00003256618,0.001095275,0.00006588169,0.001673715],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9464837,"threshold_uncertainty_score":0.999422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01312816902160474,"score_gpt":0.2421582579391864,"score_spread":0.2290300889175817,"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."}}