{"id":"W2058246935","doi":"10.1117/12.906903","title":"Lung vasculature imaging using speckle variance optical coherence tomography","year":2012,"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":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Simon Fraser University; BC Cancer Agency","funders":"Canadian Institutes of Health Research; Health Canada; St. Jude Medical; National Institutes of Health; Michael Smith Health Research BC","keywords":"Optical coherence tomography; Speckle pattern; Tomography; Biomedical engineering; Preclinical imaging; Optical tomography; Radiology; Computer science; In vivo; Medicine; Computer vision; Biology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006446263,0.0004927933,0.0005198439,0.0001873148,0.0001314765,0.0001770658,0.001130231,0.0002618672,0.00003320289],"category_scores_gemma":[0.0002443904,0.0004531984,0.0009007533,0.0009871705,0.0003966655,0.001235132,0.0001744314,0.000633753,0.000003453618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002057198,"about_ca_system_score_gemma":0.00002556285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006453425,"about_ca_topic_score_gemma":9.924475e-8,"domain_scores_codex":[0.9970963,2.462533e-8,0.0008007104,0.0004258058,0.0008140271,0.0008631376],"domain_scores_gemma":[0.9979894,0.0001803619,0.000224493,0.0001350035,0.001154367,0.0003163792],"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":[0.00002524054,0.0001507183,0.005200147,0.0005904607,0.0005610057,9.616407e-8,0.0001796226,0.001042369,0.4958352,0.4943224,0.001759887,0.0003328029],"study_design_scores_gemma":[0.002733216,0.0002274533,0.02463545,0.001389698,0.001485412,0.0001374957,0.002338955,0.6293153,0.3202263,0.005819826,0.008963669,0.002727292],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898365,0.0008234864,0.001103846,0.000460664,0.0004308585,0.0007717496,0.00005808114,0.0003182939,0.00619649],"genre_scores_gemma":[0.7718358,0.00006531427,0.2270949,0.0000518321,0.0006166373,0.0001959535,0.000008273898,0.0001024063,0.00002880348],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.628273,"threshold_uncertainty_score":0.999792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01032089995008766,"score_gpt":0.2312216519105483,"score_spread":0.2209007519604606,"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."}}