{"id":"W3126252517","doi":"10.1007/s00429-020-02211-6","title":"A comparison of diffusion tractography techniques in simulating the generalized Ising model to predict the intrinsic activity of the brain","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Excellence Research Chairs, Government of Canada","keywords":"Tractography; Ising model; Diffusion MRI; Statistical physics; Predictability; White matter; Criticality; Fractional anisotropy; Mathematics; Computer science; Artificial intelligence; Physics; Statistics; Magnetic resonance imaging","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":[],"consensus_categories":[],"category_scores_codex":[0.000130307,0.00008782325,0.0001812154,0.00005098134,0.0001196042,0.00000889333,0.00006535056,0.00005389061,0.000002963447],"category_scores_gemma":[0.0001520393,0.000044947,0.00006271576,0.0004542223,0.00007988449,0.00003787778,0.00007387131,0.0002461385,1.162501e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001196995,"about_ca_system_score_gemma":0.00002591634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002918597,"about_ca_topic_score_gemma":0.00003164927,"domain_scores_codex":[0.9993286,0.00007828377,0.0002001258,0.0001649393,0.0001429194,0.00008517029],"domain_scores_gemma":[0.9992633,0.0002076219,0.0001304076,0.0003194689,0.00005981069,0.0000194153],"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":[0.0001450926,0.00005648677,0.02864626,0.00003909361,0.00001105935,2.513986e-7,0.000681146,0.001889661,0.8608792,0.0009409001,0.0004417388,0.106269],"study_design_scores_gemma":[0.0008024157,0.0002031547,0.4873687,0.0002561437,0.000106969,0.00002579982,0.0003262307,0.08775587,0.404996,0.01473875,0.003278186,0.000141853],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9283256,0.00007445163,0.06325452,0.007709392,0.000023671,0.0005062859,0.00001004496,0.00003229607,0.00006376192],"genre_scores_gemma":[0.9952128,0.00001022427,0.003504236,0.001182046,0.00003955981,0.00001655969,0.00000479654,0.000009423433,0.00002035124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4587224,"threshold_uncertainty_score":0.1832885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04812751800487218,"score_gpt":0.352832356194857,"score_spread":0.3047048381899848,"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."}}