{"id":"W1996453211","doi":"10.1117/12.2042010","title":"Evaluation of OCT for quantitative in-vivo measurements of changes in neural tissue scattering in longitudinal studies of retinal degeneration in mice","year":2014,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Simon Fraser University; University of California, Davis; Durham University; Research to Prevent Blindness","keywords":"Optical coherence tomography; Retinal; Optics; Brightness; Normalization (sociology); Preclinical imaging; Light scattering; Materials science; Retina; Biomedical engineering; Scattering; Computer science; Ophthalmology; Medicine; In vivo; Physics; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002646407,0.001064566,0.0004943393,0.001859674,0.0004821348,0.0006998649,0.0005541822,0.001182282,0.001398229],"category_scores_gemma":[0.0008007525,0.0005884621,0.0007497304,0.0006087939,0.0005607819,0.0007838988,0.000409845,0.001875394,0.000592773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006388355,"about_ca_system_score_gemma":0.0004721741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001003622,"about_ca_topic_score_gemma":0.002462811,"domain_scores_codex":[0.9991635,0.0001842778,0.00009960608,0.0001558301,0.0002342689,0.0001625934],"domain_scores_gemma":[0.9981052,0.0003530237,0.0005445476,0.000252565,0.0003722706,0.0003722975],"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":[0.0002518964,0.0001708208,0.000255892,0.00005334298,0.00001139563,0.00004377826,0.00004637127,0.0001842109,0.9974341,0.0001687613,0.00008021817,0.001299274],"study_design_scores_gemma":[0.00005155658,0.001076101,0.003726315,0.00003309355,0.00005616919,0.0002241881,0.0000531458,0.0025789,0.9901032,0.0001227631,0.001957478,0.00001704253],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9095007,0.002865205,0.07785872,0.0005582487,0.0002882874,0.0007144643,0.00407198,0.0008465145,0.003295881],"genre_scores_gemma":[0.8637278,0.003827919,0.1155974,0.0004808631,0.00007200861,0.002258529,0.003466467,0.0005887278,0.009980359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002646407,"threshold_uncertainty_score":0.01399565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0666135792745645,"score_gpt":0.3133536330516902,"score_spread":0.2467400537771257,"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."}}