{"id":"W2520605370","doi":"10.14875/cogpsy.2009.0.7.0","title":"可変型課題切換タスクにおける加齢，日内変動，言語の効果","year":2009,"lang":"ja","type":"article","venue":"","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science","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":[0.001198708,0.0002452652,0.0001494453,0.0006100953,0.002588159,0.003883763,0.0003809876,0.001083273,0.015621],"category_scores_gemma":[0.002400464,0.0001917514,0.0001674091,0.0003654843,0.005817083,0.002195516,0.000794479,0.001337156,0.003301292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002763122,"about_ca_system_score_gemma":0.003245184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008218543,"about_ca_topic_score_gemma":0.007520982,"domain_scores_codex":[0.9992986,0.0001316485,0.00003100439,0.0001354659,0.0003214526,0.00008197223],"domain_scores_gemma":[0.9990519,0.0002692813,0.00007977222,0.00009856972,0.0003915095,0.0001090372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001945609,0.00002579768,0.0008965623,0.00004339678,0.000007940348,0.00009604758,0.003112019,0.0002721892,0.001391062,0.9547153,0.005571678,0.03384855],"study_design_scores_gemma":[0.00001818667,0.0000970421,0.005830022,0.0001452535,0.00003773376,0.0003265462,0.006803835,0.001022656,0.007187152,0.5186825,0.4598031,0.00004598432],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04256086,0.001626678,0.02158712,0.007805055,0.0006112193,0.00007405484,0.00009217091,0.00006648427,0.9255763],"genre_scores_gemma":[0.7311666,0.001490996,0.012799,0.001805761,0.0003190359,0.0000750419,0.00006974297,0.0000528032,0.252221],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.015621,"threshold_uncertainty_score":0.05225748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007796270786547305,"score_gpt":0.2048321724812804,"score_spread":0.1970359016947331,"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."}}