{"id":"W4313476595","doi":"10.15690/vsp.v21i6.2490","title":"Functional Near-Infrared Spectroscopy as Promising Method for Studying Cognitive Functions in Children","year":2023,"lang":"en","type":"article","venue":"Вопросы современной педиатрии","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children’s Health Research Institute","funders":"","keywords":"Functional near-infrared spectroscopy; Neuroimaging; Functional neuroimaging; Functional Brain Imaging; Functional magnetic resonance imaging; Functional imaging; Cognition; Electroencephalography; Psychology; Computer science; Neuroscience","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009094948,0.0003588135,0.0006048516,0.0004849568,0.0003949225,0.0001500807,0.0001213427,0.0001863195,0.0002887218],"category_scores_gemma":[0.0008137074,0.0003451991,0.0002568246,0.001203521,0.0001526465,0.000217124,0.00009605774,0.0006022833,0.0003574378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002316831,"about_ca_system_score_gemma":0.000328373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001221708,"about_ca_topic_score_gemma":0.000007856454,"domain_scores_codex":[0.9972923,0.00010273,0.000539862,0.0007859803,0.0004587421,0.0008203728],"domain_scores_gemma":[0.9985605,0.0005038172,0.000112915,0.0003576921,0.0002284977,0.0002365746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005608099,0.003234053,0.6325099,0.0004882603,0.001704314,0.000246044,0.002429228,0.0001457496,0.2079842,0.006326072,0.1155363,0.02378769],"study_design_scores_gemma":[0.01535898,0.003818957,0.8071283,0.001208292,0.00108539,0.0005562057,0.002239295,0.02119844,0.1207249,0.02020423,0.004926179,0.001550925],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8459676,0.0001740063,0.127376,0.003147057,0.0004126604,0.003715948,0.0001034949,0.001955534,0.01714773],"genre_scores_gemma":[0.8039488,0.00004772509,0.1736661,0.001884206,0.0009806296,0.001495041,0.001079431,0.0002420061,0.01665601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1746183,"threshold_uncertainty_score":0.9999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03284864591116467,"score_gpt":0.3776856270920496,"score_spread":0.3448369811808849,"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."}}