{"id":"W2973174815","doi":"","title":"表情を伴う視線による反射的視覚定位とアレキシサイミア傾向の影響 : 日本語版TAS-20を用いた検討","year":2018,"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":"Political 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","sts","insufficient_payload"],"consensus_categories":["sts"],"category_scores_codex":[0.0004375336,0.0007936277,0.0006256031,0.0003650936,0.001660115,0.0002470083,0.0009778646,0.0007052651,0.0008868631],"category_scores_gemma":[0.000695831,0.0008448982,0.0002321007,0.0008983225,0.002913599,0.001807732,0.0004571665,0.001081047,0.001859879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004795058,"about_ca_system_score_gemma":0.0007175807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008188753,"about_ca_topic_score_gemma":0.0004750445,"domain_scores_codex":[0.9959772,0.0001021707,0.00102446,0.001040948,0.0008108557,0.001044414],"domain_scores_gemma":[0.9970186,0.0002618839,0.0001553161,0.001715866,0.0005017655,0.0003465609],"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":[0.0003113937,0.0003106996,0.00200818,0.000563214,0.0007384871,0.001346318,0.0009479989,0.0006495526,0.01293783,0.9151003,0.06337965,0.001706324],"study_design_scores_gemma":[0.001719941,0.0007119665,0.004868473,0.001401602,0.0004053411,0.001596621,0.001124309,0.004882501,0.03114204,0.01088305,0.9389376,0.002326526],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2454877,0.02488544,0.01790345,0.002165469,0.04878996,0.001340515,0.006524866,0.003869499,0.6490331],"genre_scores_gemma":[0.9851042,0.0007697919,0.005157114,0.0001974727,0.005846796,0.00006902165,0.0009907272,0.00007304248,0.001791832],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9042173,"threshold_uncertainty_score":0.9997999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01426834756542856,"score_gpt":0.2404339017300442,"score_spread":0.2261655541646156,"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."}}