{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005590906,0.0003282799,0.0002789584,0.0003967561,0.000249538,0.0003394281,0.0001913765,0.0001872871,0.00300354],"category_scores_gemma":[0.001003395,0.0001252364,0.0003084804,0.000396301,0.0002717307,0.000252625,0.0002448378,0.0003934375,0.0006459505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002143669,"about_ca_system_score_gemma":0.0001770265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001404448,"about_ca_topic_score_gemma":0.003543074,"domain_scores_codex":[0.9995379,0.00009573743,0.00006862114,0.0000649563,0.0001894559,0.00004332646],"domain_scores_gemma":[0.9994473,0.0000638345,0.0002059908,0.00002452286,0.0001936718,0.00006463909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002389371,0.0006655265,0.5638642,0.0004139011,0.0004013282,0.000593694,0.002802557,0.0003301777,0.248407,0.0004320293,0.00349439,0.1762058],"study_design_scores_gemma":[0.00004863512,0.001218735,0.9784257,0.0000205315,0.0000926329,0.001187654,0.0008102491,0.0008031666,0.01455968,0.0002211851,0.002586804,0.00002503619],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934992,0.0002499844,0.001805955,0.00005577841,0.00002373824,0.0001147434,0.0002807259,0.00004016971,0.003929754],"genre_scores_gemma":[0.9900064,0.00036632,0.005904403,0.0000529803,0.00001705098,0.0002351362,0.000529552,0.00001248966,0.002875654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00300354,"threshold_uncertainty_score":0.01004785,"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."}}