{"id":"W7034642049","doi":"","title":"Végrehajtó funkciók vizsgálata fluencia feladatokkal enyhe kognitív zavarban","year":2015,"lang":"hu","type":"other","venue":"University of Debrecen Electronic Archive (University of Debrecen)","topic":"Metabolism, Diabetes, and Cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Set (abstract data type); Fluency; Quality of Life Research","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":[0.0008727883,0.0005817816,0.0005363707,0.001019111,0.001611462,0.003530236,0.0007189048,0.001178211,0.04979115],"category_scores_gemma":[0.001823409,0.000326911,0.000672029,0.0006630939,0.002385165,0.001684294,0.002451701,0.001282899,0.006806929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002114882,"about_ca_system_score_gemma":0.001905922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01000108,"about_ca_topic_score_gemma":0.01209856,"domain_scores_codex":[0.9992859,0.0001386735,0.00004320905,0.0001691008,0.0002310379,0.0001321216],"domain_scores_gemma":[0.9993497,0.0001656021,0.0001126392,0.00008184066,0.0001911002,0.00009910695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002035457,0.0007260491,0.06403604,0.002558573,0.0003616284,0.003862936,0.01887214,0.001057928,0.04842331,0.1216093,0.04828203,0.6881747],"study_design_scores_gemma":[0.00009296518,0.0006349946,0.1585851,0.001150537,0.0002821633,0.006339584,0.02161025,0.0006513954,0.01754192,0.0449914,0.7479202,0.0001996554],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4250255,0.02447778,0.01925574,0.01338375,0.001047776,0.0003277485,0.00300621,0.001051808,0.5124237],"genre_scores_gemma":[0.8152532,0.01171781,0.00987381,0.002087148,0.0002004242,0.0001950475,0.001121967,0.0002913428,0.1592593],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04979115,"threshold_uncertainty_score":0.166568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005104654655278389,"score_gpt":0.171667276553321,"score_spread":0.1665626218980426,"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."}}