{"id":"W4386192718","doi":"10.1177/20552173231195879","title":"Functional connectome fingerprinting and stability in multiple sclerosis","year":2023,"lang":"en","type":"article","venue":"Multiple Sclerosis Journal - Experimental Translational and Clinical","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Chugai Pharmaceutical; Humboldt-Universität zu Berlin; National Multiple Sclerosis Society; Deutsche Forschungsgemeinschaft; Alexion Pharmaceuticals; Teva Pharmaceutical Industries; Berlin Institute of Health; Biogen; Bayer; Arthur Arnstein Stiftung; Guthy-Jackson Charitable Foundation; Sanofi","keywords":"Connectome; Human Connectome Project; Resting state fMRI; Neuroscience; Multiple sclerosis; Default mode network; Cognition; Psychology; Functional connectivity; Identification (biology); Biology; Psychiatry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001576515,0.0002822943,0.0004267054,0.0002229299,0.0008773819,0.0001671788,0.0001388929,0.000145263,0.000189874],"category_scores_gemma":[0.005440291,0.0002666668,0.0002166382,0.0004769424,0.0006057597,0.0005569717,0.0001579202,0.0006432473,0.00004256356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006944533,"about_ca_system_score_gemma":0.00005906916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003472887,"about_ca_topic_score_gemma":0.0000804888,"domain_scores_codex":[0.9967058,0.0004501475,0.0009344075,0.0008340618,0.0006279885,0.0004475496],"domain_scores_gemma":[0.9840754,0.01529655,0.0001707414,0.0001381998,0.0000663685,0.000252785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007180379,0.0006453111,0.6204849,0.00001742717,0.00004426943,0.0000128393,0.0007859693,0.0002028595,0.3705855,0.0005450205,0.0002719641,0.005685944],"study_design_scores_gemma":[0.00484885,0.0002089662,0.9467013,0.0001047032,0.00001189032,0.00004519066,0.000887907,0.00981553,0.03578028,0.001060156,0.0002195188,0.0003156931],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928225,0.0003741396,0.0001724507,0.005402887,0.0006821061,0.0002868275,0.00006361988,0.0001016943,0.00009383336],"genre_scores_gemma":[0.9978061,0.0004916372,0.0004029646,0.000889301,0.0003107341,0.00004328123,0.000008999276,0.00002810356,0.00001892611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3348052,"threshold_uncertainty_score":0.9999785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3528472419169832,"score_gpt":0.3436057157677416,"score_spread":0.009241526149241674,"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."}}