{"id":"W4408592040","doi":"10.34922/ae.2024.37.6.007","title":"КЛИНИЧЕСКИЕ ДЕТЕРМИНАНТЫ ДЛЯ ТАРГЕТНОГО ВОЗДЕЙСТВИЯ НЕЙРОКОГНИТИВНОЙ РЕАБИЛИТАЦИИ У ПАЦИЕНТОВ ПОЖИЛОГО И СТАРЧЕСКОГО ВОЗРАСТА С МЯГКИМ КОГНИТИВНЫМ СНИЖЕНИЕМ","year":2025,"lang":"ru","type":"article","venue":"Успехи геронтологии","topic":"Neurological Disease Mechanisms and Treatments","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer 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":[0.002694034,0.0007866499,0.0005404722,0.002668294,0.0037749,0.01111844,0.00134375,0.002242873,0.04532218],"category_scores_gemma":[0.007963019,0.000892761,0.0008303496,0.00233692,0.005581859,0.006189108,0.003496913,0.003072849,0.01424691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004051674,"about_ca_system_score_gemma":0.007114342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008040133,"about_ca_topic_score_gemma":0.00818124,"domain_scores_codex":[0.9954091,0.001196852,0.0002384146,0.000810809,0.001840621,0.0005042906],"domain_scores_gemma":[0.9963798,0.0009590989,0.0003327616,0.0006568784,0.001294883,0.0003765404],"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":[0.00009622066,0.00005663225,0.001896223,0.0003007425,0.0000311297,0.0004812704,0.004055875,0.0010061,0.003070156,0.8902133,0.01467047,0.08412187],"study_design_scores_gemma":[0.0000335337,0.00006039597,0.002775808,0.0003539758,0.00004760613,0.000778559,0.004660687,0.001262489,0.003524364,0.256239,0.7301756,0.00008800392],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03653118,0.01057936,0.07837621,0.01238246,0.00183215,0.0003094125,0.00104257,0.0005111134,0.8584355],"genre_scores_gemma":[0.6511093,0.01481735,0.08832228,0.002413388,0.000991755,0.000877735,0.001322312,0.0008254803,0.2393204],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04532218,"threshold_uncertainty_score":0.1516178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02410797652996655,"score_gpt":0.2918116059979013,"score_spread":0.2677036294679348,"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."}}