{"id":"W2049135268","doi":"10.1016/j.jqsrt.2010.08.030","title":"New developments in frequency domain optical tomography. Part I: Forward model and gradient computation","year":2010,"lang":"en","type":"article","venue":"Journal of Quantitative Spectroscopy and Radiative Transfer","topic":"Numerical methods in inverse problems","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada; Université du Québec à Chicoutimi","funders":"","keywords":"Computation; Adjoint equation; Tomography; Optical tomography; Domain (mathematical analysis); Computer science; Formalism (music); Frequency domain; Finite element method; Applied mathematics; Boundary value problem; Collimated light; Mathematical analysis; Algorithm; Physics; Mathematics; Partial differential equation; Optics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006670433,0.0006996435,0.0006731908,0.0007338347,0.0002024929,0.001209117,0.0008487955,0.0009411447,0.002074415],"category_scores_gemma":[0.002058878,0.0004497611,0.0007181903,0.0008795719,0.001184449,0.003072129,0.001069657,0.001836468,0.0007686144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000558444,"about_ca_system_score_gemma":0.0005031746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008258735,"about_ca_topic_score_gemma":0.0007888502,"domain_scores_codex":[0.9997408,0.00007307551,0.00001770861,0.00004596752,0.0001078823,0.00001449918],"domain_scores_gemma":[0.9994076,0.0002905388,0.00003502454,0.0001249692,0.0001146771,0.00002709585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007884655,0.0000974646,0.000537657,0.0007565751,0.00007793443,0.00009848698,0.0001266235,0.07117379,0.0204287,0.5187817,0.01317947,0.3746627],"study_design_scores_gemma":[0.00001795429,0.00007774024,0.0005543082,0.0001279728,0.00003130266,0.0003966414,0.00003407126,0.5524167,0.005610613,0.3658772,0.07480617,0.00004935433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004344188,0.02864621,0.9567996,0.002967135,0.0008873497,0.00001922373,0.00007099298,0.0002405496,0.006024855],"genre_scores_gemma":[0.1387604,0.06781141,0.7687304,0.001052047,0.002966581,0.0001320366,0.000203578,0.0004348898,0.01990863],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002074415,"threshold_uncertainty_score":0.00693965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05353636571395736,"score_gpt":0.3635373774595154,"score_spread":0.3100010117455581,"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."}}