{"id":"W2021322342","doi":"10.1109/tbme.2008.926680","title":"Selection Criteria for the Analysis of Data-Driven Clusters in Cerebral fMRI","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Carleton University; Ottawa Hospital; Royal Ottawa Mental Health Centre","funders":"","keywords":"Selection (genetic algorithm); Artificial intelligence; Computer science; Parametric statistics; Cluster analysis; Interpretation (philosophy); Statistical parametric mapping; Pattern recognition (psychology); Voxel; Contiguity; Data mining; Mathematics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01145981,0.001310888,0.001570217,0.00263305,0.001222,0.0017386,0.001762542,0.001325887,0.001306873],"category_scores_gemma":[0.058874,0.0006153003,0.001299134,0.00163043,0.001346631,0.001202612,0.001823326,0.001298569,0.0003952333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008867435,"about_ca_system_score_gemma":0.002717667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001325231,"about_ca_topic_score_gemma":0.00257077,"domain_scores_codex":[0.9941399,0.002438622,0.0006687517,0.0007415871,0.001785409,0.0002257848],"domain_scores_gemma":[0.9647333,0.02593101,0.001836127,0.001680816,0.005375005,0.0004437165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001735106,0.0004599301,0.01576232,0.001221037,0.0006025826,0.001286346,0.001465726,0.1686634,0.0746211,0.0550263,0.005263792,0.6738924],"study_design_scores_gemma":[0.000263921,0.0004231078,0.008362237,0.00009514703,0.0001324054,0.0003812092,0.0002037755,0.9214873,0.03528524,0.02809856,0.005124395,0.000142537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01607476,0.00004686332,0.9828752,0.00006746053,0.0000105367,0.0002714711,0.00006806151,0.0004018251,0.0001838411],"genre_scores_gemma":[0.09678257,0.00003466713,0.9011286,0.00004994771,0.0000253589,0.001164742,0.0003788249,0.0002477015,0.0001876801],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01145981,"threshold_uncertainty_score":0.060606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06687940089633253,"score_gpt":0.2979538549769456,"score_spread":0.2310744540806131,"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."}}