{"id":"W4402281454","doi":"10.1101/2024.09.03.610819","title":"Personalized models of Disorders of Consciousness reveal complementary roles of connectivity and local parameters in diagnosis and prognosis","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Dimension (graph theory); Neuroimaging; Dimensionality reduction; Variety (cybernetics); Computer science; Node (physics); Consciousness; Pipeline (software); Artificial intelligence; Persistent vegetative state; Machine learning; Curse of dimensionality; Space (punctuation); Psychology; Data science; Data mining; Neuroscience; Mathematics","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":[0.0008074543,0.0005979035,0.0005590247,0.0006850953,0.0002196158,0.001108524,0.0005766011,0.0006571051,0.001418103],"category_scores_gemma":[0.002652393,0.0003201417,0.0006820672,0.000420575,0.0005882285,0.00108766,0.0005880435,0.00106755,0.0002998058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005485367,"about_ca_system_score_gemma":0.000482397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003552629,"about_ca_topic_score_gemma":0.003563866,"domain_scores_codex":[0.9997458,0.00009870611,0.00001036482,0.00008256995,0.00002770047,0.00003490132],"domain_scores_gemma":[0.9994006,0.0003291001,0.0001096215,0.00008061938,0.00004293738,0.00003710973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002514626,0.0001497807,0.02564322,0.0001355031,0.0003094563,0.0003540684,0.0003963322,0.8235472,0.009079577,0.06993777,0.002838971,0.06735653],"study_design_scores_gemma":[0.000007683339,0.00003462283,0.007190606,0.00001605848,0.00003981952,0.00009108878,0.0000368889,0.9453074,0.0004108901,0.04626327,0.0005791504,0.00002243157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2698415,0.001208584,0.722357,0.002013877,0.00006447461,0.00005353065,0.001316101,0.0004236312,0.002721382],"genre_scores_gemma":[0.972403,0.000779173,0.02389078,0.0001016492,0.00005684192,0.00007256144,0.0004837037,0.00005238131,0.00215993],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003552629,"threshold_uncertainty_score":0.007063866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0323735963758699,"score_gpt":0.2484480408895949,"score_spread":0.216074444513725,"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."}}