{"id":"W1967113208","doi":"10.1016/j.media.2010.04.006","title":"Wavelet-based estimation of the hemodynamic responses in diffuse optical imaging","year":2010,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Wavelet; Diffuse optical imaging; Estimator; Computer science; Artificial intelligence; SIGNAL (programming language); Noise (video); Finger tapping; Contrast (vision); Functional near-infrared spectroscopy; Computer vision; Pattern recognition (psychology); Mathematics; Image (mathematics); Neuroscience; Iterative reconstruction; Statistics; Cognition; Psychology; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008479847,0.000141031,0.0004635305,0.0004263191,0.00004536595,0.00002559627,0.0002288752,0.0001075921,0.0003875348],"category_scores_gemma":[0.004622578,0.000090799,0.0003149874,0.001258201,0.0006596774,0.00007145124,0.00006582106,0.0007527487,0.000006923195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004792353,"about_ca_system_score_gemma":0.0001879054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001644284,"about_ca_topic_score_gemma":0.0001034887,"domain_scores_codex":[0.9981496,0.00009553743,0.0004537766,0.0002729819,0.0007609321,0.0002671299],"domain_scores_gemma":[0.9986625,0.0003578381,0.00007888972,0.0006022751,0.00010136,0.0001971172],"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":[0.000603183,0.004648738,0.3184947,0.0002627791,0.0005887013,0.0007402138,0.0002315567,0.00003307749,0.5651149,0.002299051,0.000683064,0.1063],"study_design_scores_gemma":[0.00100522,0.00003345411,0.138901,0.00008536357,0.0007647573,0.00001899697,0.00001947227,0.8039483,0.05479324,0.0002949702,0.00002703657,0.0001081163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8905002,0.0000186423,0.09358928,0.01447409,0.00004157602,0.0001373354,0.000003712672,0.00008283911,0.001152334],"genre_scores_gemma":[0.9376581,0.000004700211,0.06136905,0.0007905439,0.00002819013,0.00001275569,0.00001524211,0.00001387172,0.0001075204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8039153,"threshold_uncertainty_score":0.5533991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004223334705785716,"score_gpt":0.3080096687362906,"score_spread":0.3037863340305049,"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."}}