{"id":"W7132974855","doi":"","title":"Machine Learning Perspectives in Compression, Distributed Computing, and Brain Imaging","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Gaussian Processes and Bayesian Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Leverage (statistics); Exploit; Coding (social sciences); Gaussian process; Probabilistic logic; Inference; Process (computing); Subnetwork; Neuroimaging","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":[0.003231529,0.001103396,0.001052277,0.00133338,0.0005943882,0.00340611,0.001965066,0.002384161,0.002841192],"category_scores_gemma":[0.007588745,0.0004472545,0.0008264706,0.002392846,0.004450589,0.005782571,0.001881612,0.00522462,0.0006628952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001921991,"about_ca_system_score_gemma":0.001076411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001779372,"about_ca_topic_score_gemma":0.0009721043,"domain_scores_codex":[0.9983656,0.0006455359,0.00008088603,0.0002832834,0.0005010079,0.0001236653],"domain_scores_gemma":[0.9940567,0.004463632,0.0002252484,0.0006602299,0.0004868972,0.0001071934],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006587704,0.00005685438,0.000555378,0.0003463096,0.00004725833,0.0001347503,0.0002336458,0.05973985,0.001550689,0.8283016,0.005170916,0.1037967],"study_design_scores_gemma":[0.00002454738,0.0000895104,0.0004103629,0.0001381502,0.00001413165,0.0001787611,0.00008759197,0.237413,0.00157118,0.7373664,0.02267597,0.00003043057],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008147778,0.0381115,0.9175181,0.01942036,0.001115437,0.0000640342,0.0001401288,0.0003006914,0.01518205],"genre_scores_gemma":[0.4313792,0.05778877,0.4794565,0.004945737,0.01159283,0.0005737877,0.00033177,0.0002489378,0.01368237],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00340611,"threshold_uncertainty_score":0.01709014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01126774290228543,"score_gpt":0.3202973159932543,"score_spread":0.3090295730909688,"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."}}