{"id":"W4229013045","doi":"10.1101/2022.05.03.490534","title":"Multi-view manifold learning of human brain state trajectories","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Nonlinear dimensionality reduction; Dimensionality reduction; Curse of dimensionality; Computer science; Artificial intelligence; Pattern recognition (psychology); Redundancy (engineering); Data point; Machine learning; Functional magnetic resonance imaging; Manifold (fluid mechanics); Population","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":[0.0007187521,0.0006782484,0.0004570348,0.001103028,0.0003837355,0.0007841297,0.0005561467,0.0008614624,0.001451226],"category_scores_gemma":[0.003706404,0.0003492091,0.0009450719,0.0006536956,0.0007001297,0.001091936,0.0008664899,0.001227846,0.0004413352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006185698,"about_ca_system_score_gemma":0.00055952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006131443,"about_ca_topic_score_gemma":0.0062029,"domain_scores_codex":[0.9997509,0.00007837157,0.000009547474,0.00009707693,0.00003542165,0.00002874697],"domain_scores_gemma":[0.9993786,0.0003052923,0.00006946219,0.000104582,0.00009648893,0.00004557106],"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":[0.00031029,0.0001158231,0.006468464,0.0001478724,0.0001721842,0.0002687094,0.0005984254,0.7406392,0.01482007,0.02389249,0.005796215,0.2067703],"study_design_scores_gemma":[0.000002734226,0.00001244968,0.001120645,0.000004511017,0.000002954819,0.00003350697,0.00002521667,0.9880987,0.0008292177,0.009518405,0.0003435303,0.000008259978],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1667202,0.0005513119,0.8290737,0.0007853757,0.00006099351,0.00006627738,0.0005296508,0.0009780624,0.001234371],"genre_scores_gemma":[0.8661311,0.0005342583,0.1291832,0.00007922591,0.00006392189,0.00008193437,0.001382377,0.0001905889,0.002353383],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006131443,"threshold_uncertainty_score":0.01219147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03942610559519025,"score_gpt":0.2645178107344362,"score_spread":0.225091705139246,"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."}}