{"id":"W7145922598","doi":"","title":"韓国江原道における現職教員再教育","year":2006,"lang":"ja","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Educational Research and Pedagogy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Foreign language; English language; Training (meteorology); Primary education; National education","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002725348,0.0002857328,0.0003292591,0.002302288,0.001407214,0.003401442,0.000483219,0.0005244834,0.01043548],"category_scores_gemma":[0.005397835,0.00051094,0.0003699094,0.002437771,0.001851235,0.003461418,0.001077258,0.0009053599,0.008830232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008998184,"about_ca_system_score_gemma":0.002230686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004722971,"about_ca_topic_score_gemma":0.007202945,"domain_scores_codex":[0.9978083,0.0003749176,0.0003380596,0.0003295599,0.0009564954,0.0001927313],"domain_scores_gemma":[0.9940405,0.001538135,0.0006873323,0.0009702918,0.002449045,0.0003146774],"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":[0.0005377945,0.0003361653,0.04614877,0.0009816928,0.00009511722,0.002436684,0.005533913,0.0008027089,0.0359752,0.04530838,0.06485666,0.7969869],"study_design_scores_gemma":[0.00007745257,0.0003688553,0.06538282,0.0005309778,0.0001878723,0.005863314,0.009725389,0.0028199,0.06583277,0.02820196,0.8208327,0.0001760582],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3827968,0.01313771,0.1216444,0.01118646,0.002007111,0.0006226256,0.01371176,0.00318715,0.4517061],"genre_scores_gemma":[0.7879406,0.01311424,0.09221429,0.001779241,0.0006612528,0.0003781001,0.01494388,0.0006485586,0.08831984],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01043548,"threshold_uncertainty_score":0.0349102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03268706757889617,"score_gpt":0.3159743486376638,"score_spread":0.2832872810587677,"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."}}