{"id":"W4220658420","doi":"10.1002/hbm.25801","title":"Monofractal analysis of functional magnetic resonance imaging: An introductory review","year":2022,"lang":"en","type":"review","venue":"Human Brain Mapping","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"BC Children's Hospital","keywords":"Functional magnetic resonance imaging; Hurst exponent; Multifractal system; Neuroimaging; Artificial intelligence; Neuroscience; Computer science; Fractal; Psychology; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001830864,0.0004661868,0.004239146,0.001988186,0.0003573909,0.00007588374,0.0006601109,0.00009162651,0.03844228],"category_scores_gemma":[0.0001846769,0.0005457597,0.001946477,0.003004454,0.00009676694,0.0002011147,0.0002680873,0.0004255448,0.0001037613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002851458,"about_ca_system_score_gemma":0.00006380746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004785298,"about_ca_topic_score_gemma":0.00006032512,"domain_scores_codex":[0.9956409,0.0002087273,0.002495826,0.00113734,0.00014723,0.0003700053],"domain_scores_gemma":[0.9962901,0.0001839137,0.002021061,0.001346935,0.00005303065,0.0001049637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002625321,0.0001694521,0.000534411,0.02299986,0.002332731,0.00001654109,0.0001923849,0.00003354249,0.000001215347,0.04711474,0.01818862,0.9084139],"study_design_scores_gemma":[0.0000767555,0.00003065851,0.001648377,0.002013026,0.001390904,0.000007635626,0.00005047786,0.0005176521,1.293073e-9,0.0004338432,0.993323,0.0005077054],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000009667438,0.9945,0.0001915178,0.0001000416,0.000224911,0.0004478627,0.0004355689,0.00004112471,0.004049325],"genre_scores_gemma":[0.00004833591,0.9942417,0.0000624188,0.0002333473,0.0003304848,0.0001609207,0.001481152,0.00006883819,0.003372872],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9751343,"threshold_uncertainty_score":0.9996994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1084660348120241,"score_gpt":0.2851684388658792,"score_spread":0.1767024040538551,"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."}}