{"id":"W7028439534","doi":"","title":"Exploring functional brain networks using independent component analysis:functional brain networks connectivity","year":2013,"lang":"en","type":"dissertation","venue":"University of Oulu Repository (University of Oulu)","topic":"Environmental Science and Technology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Independent component analysis; Functional connectivity; Functional integration; Aggregate (composite); Cognition; Human brain; Component (thermodynamics); Function (biology)","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":[0.0002252004,0.0002814228,0.0004820521,0.000311638,0.0005632438,0.00001286948,0.0004653129,0.000635533,0.000178876],"category_scores_gemma":[0.00001270539,0.000397934,0.000494929,0.0003892627,0.0003907744,0.00006989312,0.0002966057,0.0003905871,0.000003976986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001925841,"about_ca_system_score_gemma":0.0001163293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00141447,"about_ca_topic_score_gemma":0.0008793242,"domain_scores_codex":[0.9982529,0.0001520557,0.0001958114,0.000701101,0.0003926725,0.0003054767],"domain_scores_gemma":[0.9986414,0.0000499481,0.0005832925,0.0004396408,0.0001491182,0.0001366479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001788653,0.000859415,0.06300113,0.0001473748,0.005147126,0.0002716027,0.00089814,0.2869039,0.63332,0.0003837389,0.005017645,0.002261346],"study_design_scores_gemma":[0.002900646,0.0007712999,0.8877901,0.0001786939,0.002616507,0.00009247535,0.03193305,0.04860422,0.0182308,0.00002770725,0.005262006,0.001592491],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9658034,0.0001864738,0.0320473,0.00007298285,0.000508168,0.0002084717,0.00001700898,0.00002501608,0.001131132],"genre_scores_gemma":[0.991816,0.000109435,0.0003604062,0.00001601345,0.00009147156,2.008103e-7,0.0009320279,0.00001535799,0.006659064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.824789,"threshold_uncertainty_score":0.9998472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02182134269403787,"score_gpt":0.1863309814277034,"score_spread":0.1645096387336655,"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."}}