{"id":"W3024042329","doi":"10.1364/boe.392113","title":"Characterizing dynamic cerebral vascular reactivity using a hybrid system combining time-resolved near-infrared and diffuse correlation spectroscopy","year":2020,"lang":"en","type":"article","venue":"Biomedical Optics Express","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Oxygenation; Blood flow; Cerebral blood flow; Near-infrared spectroscopy; Scalp; Biomedical engineering; Blood volume; Medicine; Nuclear magnetic resonance; Cardiology; Internal medicine; Neuroscience; Surgery; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002655428,0.0003076609,0.0006776943,0.00009251789,0.0002002532,0.0001744965,0.0001369101,0.000179146,0.00002494486],"category_scores_gemma":[0.0002892325,0.0002846621,0.0001322301,0.0002227529,0.0003833638,0.000205827,0.0001740453,0.000571446,0.00001918455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001924934,"about_ca_system_score_gemma":0.00009561104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003070313,"about_ca_topic_score_gemma":4.787813e-8,"domain_scores_codex":[0.9978172,0.00009633738,0.0004710894,0.0005682139,0.0005568885,0.0004902234],"domain_scores_gemma":[0.9986057,0.0001191043,0.0001618829,0.0003626734,0.00007524037,0.0006753856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001787336,0.0002605443,0.001050654,0.0003604317,0.00009610502,0.0001732434,0.0003396165,0.000001896688,0.9968566,0.000158819,0.0001015641,0.0004217357],"study_design_scores_gemma":[0.002323547,0.0005671949,0.001469251,0.000709313,0.0002802541,0.0001329323,0.00008219022,0.9544008,0.03907192,0.00004627596,0.0005694507,0.0003468976],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8186413,0.0001009251,0.1786644,0.0009351898,0.0001448936,0.0004680112,0.00003598987,0.0006244398,0.0003848704],"genre_scores_gemma":[0.8954071,0.00002762334,0.1037451,0.0003986526,0.0001805917,0.00001332544,0.0001328734,0.0000629886,0.00003171114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9577847,"threshold_uncertainty_score":0.9999605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01376507476414684,"score_gpt":0.2662368488005364,"score_spread":0.2524717740363895,"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."}}