{"id":"W1978001957","doi":"10.1371/journal.pone.0028817","title":"Resting-State Brain Organization Revealed by Functional Covariance Networks","year":2011,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University; NYU Langone Medical Center","keywords":"Default mode network; Covariance; Resting state fMRI; Task (project management); Computer science; Functional connectivity; Neuroscience; Network analysis; Cognition; State (computer science); Human brain; Correlation; Modular design; Pattern recognition (psychology); Psychology; Artificial intelligence; Mathematics; Statistics; Algorithm; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0004028892,0.0001776174,0.0001507272,0.0006736963,0.0001510038,0.0003688171,0.0002179707,0.000199569,0.0007626524],"category_scores_gemma":[0.002222756,0.0001215457,0.000203243,0.0005458276,0.0004349946,0.0006462774,0.0002346317,0.000236686,0.00006508711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003567218,"about_ca_system_score_gemma":0.0001920498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001175181,"about_ca_topic_score_gemma":0.001974292,"domain_scores_codex":[0.9998429,0.00004331964,0.000007864063,0.00006257834,0.00002427538,0.00001895596],"domain_scores_gemma":[0.9993851,0.0003043771,0.0001515318,0.00005500285,0.00006373752,0.00004014443],"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":[0.001017733,0.0002893989,0.2716262,0.0003675901,0.0007075012,0.0007889826,0.001569501,0.06260879,0.4318421,0.02920715,0.00171788,0.1982573],"study_design_scores_gemma":[0.00002276154,0.0001697415,0.7141311,0.00001970154,0.0001440162,0.0007561131,0.0001613451,0.2351756,0.01719697,0.03107258,0.001093201,0.00005691127],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.890305,0.0002662942,0.1064783,0.0001387123,0.00000807464,0.0000349999,0.0004509619,0.0001276089,0.00219008],"genre_scores_gemma":[0.9938642,0.00005344331,0.005759504,0.000007189111,0.000007112217,0.00001667408,0.0001727956,0.000009769865,0.0001093071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001175181,"threshold_uncertainty_score":0.002588212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09544155821001803,"score_gpt":0.2142652500798543,"score_spread":0.1188236918698362,"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."}}