{"id":"W4392725786","doi":"10.1101/2024.03.06.583728","title":"Comparison of compartmental analytical BOLD fMRI models against Monte Carlo simulations performed over cortical micro-angiograms","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre hospitalier de l'Université Laval; Université de Sherbrooke; Université Laval","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada","keywords":"Monte Carlo method; Amplitude; Contrast (vision); Physics; Statistical physics; Computer science; Nuclear magnetic resonance; Artificial intelligence; Mathematics; Optics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006679925,0.0006493478,0.0006190367,0.0005428947,0.0003421507,0.000714043,0.001024622,0.00133371,0.001378979],"category_scores_gemma":[0.004014024,0.0003487803,0.0005663924,0.0005295986,0.0004458914,0.0005366965,0.0002787401,0.0007825796,0.0002537426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001129964,"about_ca_system_score_gemma":0.001023831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02360415,"about_ca_topic_score_gemma":0.0104806,"domain_scores_codex":[0.99981,0.00007698094,0.00001268738,0.00002970357,0.0000418481,0.00002879628],"domain_scores_gemma":[0.9968184,0.002503768,0.0002054193,0.0001424666,0.0002496236,0.00008014932],"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":[0.00006655779,0.00002118894,0.0003646466,0.00002634465,0.0000156973,0.00003511713,0.00002400492,0.9958007,0.001379413,0.001051713,0.0001377761,0.001076794],"study_design_scores_gemma":[0.000003490487,0.000006436349,0.00009630417,0.000002062817,0.000002363996,0.000004904396,0.000003619767,0.9991949,0.0004271472,0.0002143247,0.00004097403,0.000003394747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7036152,0.0008514859,0.28311,0.0008566319,0.0001002889,0.0001455862,0.0009030897,0.00220158,0.008216113],"genre_scores_gemma":[0.9798749,0.0002082045,0.01843464,0.00009846616,0.00001588242,0.0001068589,0.0002064602,0.0001933501,0.0008612538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02360415,"threshold_uncertainty_score":0.04693353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03909241876080631,"score_gpt":0.3312328603815495,"score_spread":0.2921404416207432,"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."}}