{"id":"W2062049965","doi":"10.1364/ol.37.002571","title":"Model-independent dynamic constraint to improve the optical reconstruction of regional kinetic parameters","year":2012,"lang":"en","type":"article","venue":"Optics Letters","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Ontario Neurotrauma Foundation; Heart and Stroke Foundation of Canada","keywords":"Deconvolution; Inverse problem; Kinetic energy; Optics; Iterative reconstruction; Computer science; Biological system; Constraint (computer-aided design); Algorithm; Materials science; Physics; Mathematics; Computer vision; Mathematical analysis","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":[],"consensus_categories":[],"category_scores_codex":[0.0002735637,0.0001523054,0.0002414372,0.00008945976,0.00004457302,0.00002046405,0.0001079148,0.00007300272,0.0000128409],"category_scores_gemma":[0.00009377544,0.0001096946,0.0001164935,0.0001052633,0.0003960643,0.00006726965,0.00004274314,0.0003212605,0.00001217879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001188794,"about_ca_system_score_gemma":0.00003751984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009996,"about_ca_topic_score_gemma":7.553666e-7,"domain_scores_codex":[0.9987911,0.00002401584,0.0002955127,0.0001993945,0.0003070375,0.0003829517],"domain_scores_gemma":[0.9992015,0.00009062299,0.00006745553,0.000359601,0.00006401625,0.0002167431],"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":[0.0001284862,0.0001757078,0.001366596,0.00005141484,0.00009396479,0.000007025483,0.0002712896,0.0005652043,0.9752587,0.01263014,0.0007304921,0.008720969],"study_design_scores_gemma":[0.003496886,0.002116253,0.01466983,0.0008388676,0.001495831,0.002696516,0.001269354,0.5398658,0.4281744,0.003207887,0.0005994017,0.001568941],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8717727,0.00002701737,0.1054421,0.02037906,0.0002098854,0.0004075027,0.000005554214,0.00006997875,0.001686175],"genre_scores_gemma":[0.7523097,0.00001219629,0.2446105,0.002929584,0.00004864387,0.00002117068,0.000003539936,0.00001664018,0.00004804534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5470843,"threshold_uncertainty_score":0.4473216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01940541560744354,"score_gpt":0.2901582599252764,"score_spread":0.2707528443178329,"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."}}