{"id":"W1996630013","doi":"10.1002/hbm.20623","title":"Parcellation‐dependent small‐world brain functional networks: A resting‐state fMRI study","year":2008,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":672,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Key Research and Development Program of China; National High-tech Research and Development Program; National Natural Science Foundation of China","keywords":"Resting state fMRI; Neuroscience; Functional connectivity; Thresholding; Human brain; Neuroimaging; Degree distribution; Complex network; Small-world network; Psychology; Artificial intelligence; Pattern recognition (psychology); Computer science","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","sts"],"consensus_categories":[],"category_scores_codex":[0.001279822,0.0004165341,0.0004046929,0.0005020917,0.003010112,0.0001361352,0.0003740225,0.000059172,0.0002808023],"category_scores_gemma":[0.007024882,0.0004471662,0.0001509591,0.001018397,0.0003150506,0.0002778687,0.0004124177,0.00057432,0.0001663253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002145359,"about_ca_system_score_gemma":0.00008208855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009686314,"about_ca_topic_score_gemma":0.0008315313,"domain_scores_codex":[0.9958249,0.0007198402,0.0006377435,0.001271529,0.0008294586,0.0007164924],"domain_scores_gemma":[0.9887555,0.01009429,0.000294285,0.0005721161,0.0001279774,0.0001558091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003974441,0.002227838,0.2575583,0.0001215166,0.0003279553,0.001523769,0.01447813,0.1171127,0.2045053,0.01145663,0.3881212,0.002169307],"study_design_scores_gemma":[0.003125543,0.0004548064,0.9395958,0.0001134244,0.00002281371,0.0002452056,0.001089968,0.007584327,0.0004400028,0.005943105,0.04020864,0.00117634],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9569551,0.00007129989,0.01370182,0.01231152,0.0009932541,0.001331688,0.00000906271,0.0007207712,0.01390547],"genre_scores_gemma":[0.9610714,0.000004072426,0.0001392806,0.008824601,0.0007791719,0.0001418206,0.000009037012,0.00006293001,0.02896774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6820376,"threshold_uncertainty_score":0.999798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1276827600574583,"score_gpt":0.2785235060700825,"score_spread":0.1508407460126242,"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."}}