{"id":"W2036087924","doi":"10.1364/boe.2.002068","title":"Calibration of diffuse correlation spectroscopy with a time-resolved near-infrared technique to yield absolute cerebral blood flow measurements","year":2011,"lang":"en","type":"erratum","venue":"Biomedical Optics Express","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":126,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lawson Health Research Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Near-infrared spectroscopy; Cerebral blood flow; Indocyanine green; Blood flow; Photon diffusion; Diffuse optical imaging; Materials science; Calibration; Correlation coefficient; Neurointensive care; Biomedical engineering; Nuclear magnetic resonance; Perfusion; Spectroscopy; Medicine; Nuclear medicine; Optics; Pathology; Anesthesia; Physics; Cardiology; Radiology; Computer science; Tomography; Nanotechnology","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":[0.002311331,0.001015096,0.0004873326,0.0009408327,0.0002762862,0.0005417448,0.0009121395,0.0009841125,0.003573067],"category_scores_gemma":[0.00632125,0.0004524663,0.0003705674,0.001410142,0.000535392,0.000830703,0.0004728673,0.001108097,0.001985464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004750641,"about_ca_system_score_gemma":0.0005319471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009901592,"about_ca_topic_score_gemma":0.0026114,"domain_scores_codex":[0.998591,0.0003220679,0.00007260103,0.0003788713,0.0005909386,0.00004454302],"domain_scores_gemma":[0.998651,0.0005066718,0.0001417029,0.0002382099,0.0004370628,0.00002551228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002633618,0.0001262965,0.003802662,0.0005454542,0.00005317829,0.0002931479,0.0001889063,0.001373773,0.836613,0.002412833,0.005022653,0.1493048],"study_design_scores_gemma":[0.00007780109,0.001202908,0.01842518,0.0001381322,0.0001578383,0.002120727,0.0001883012,0.03528536,0.8813651,0.001350987,0.05957296,0.0001148226],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.1663754,0.008508175,0.8026359,0.001127116,0.004688628,0.0003379032,0.0007305347,0.002453006,0.01314331],"genre_scores_gemma":[0.3059883,0.007915142,0.6629146,0.0006515765,0.0001667379,0.0004357283,0.0008675649,0.0005112087,0.02054916],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.003573067,"threshold_uncertainty_score":0.01222366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02206312903437706,"score_gpt":0.2670180109148827,"score_spread":0.2449548818805056,"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."}}