{"id":"W2016042019","doi":"10.1088/0031-9155/54/23/005","title":"A comprehensive study of the use of temporal moments in time-resolved diffuse optical tomography: part II. Three-dimensional reconstructions","year":2009,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Moment (physics); Photon; Diffuse optical imaging; Inverse; Inverse problem; Transmission (telecommunications); Optics; Quality (philosophy); Tomography; Second moment of area; Physics; Iterative reconstruction; Computational physics; Mathematics; Computer science; Mathematical analysis; Geometry; Computer vision; Telecommunications; Classical mechanics","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":[0.00008469138,0.0001059125,0.0004651893,0.000107354,0.0000280767,0.000001374641,0.00006353786,0.00005604819,0.000007795201],"category_scores_gemma":[0.00006368417,0.00006226604,0.00003835751,0.0002946107,0.0005300652,0.00002729218,0.00005600779,0.000242489,1.400392e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000115281,"about_ca_system_score_gemma":0.00001934763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002669606,"about_ca_topic_score_gemma":0.00002984067,"domain_scores_codex":[0.9991661,0.00006039969,0.0003426646,0.0001798134,0.0001088939,0.0001421558],"domain_scores_gemma":[0.9994774,0.0001393308,0.00007521942,0.0001980674,0.00006804831,0.00004185922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000355097,0.003650944,0.9190267,0.00002495973,0.00007286115,0.000008725431,0.0003886118,0.000008512113,0.06801399,0.001837019,0.0004072574,0.006205301],"study_design_scores_gemma":[0.0119847,0.01417743,0.9321401,0.001101512,0.0002620492,0.00004539505,0.0005037396,0.003681278,0.006709459,0.02862122,0.0004874411,0.0002856503],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980219,0.00007288151,0.00003780613,0.001366687,0.000047538,0.0003620384,0.000004209588,0.00001305363,0.00007386093],"genre_scores_gemma":[0.9979181,0.00002255128,0.001614393,0.0003640106,0.00004909876,0.000007328975,0.000009156801,0.000003881625,0.00001151462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06130453,"threshold_uncertainty_score":0.2539136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.172758409956033,"score_gpt":0.3877139004465212,"score_spread":0.2149554904904882,"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."}}