{"id":"W4381516769","doi":"10.1364/boda.2023.dm4a.4","title":"Multipath Artifacts in Co-registered Optical Coherence Tomography and Autofluorescence Imaging Provide Biomarkers for Ovarian Cancer Detection","year":2023,"lang":"en","type":"article","venue":"","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; Vancouver General Hospital; University of British Columbia","funders":"","keywords":"Optical coherence tomography; Autofluorescence; Ovarian cancer; Ex vivo; Multipath propagation; Cancer detection; Computer science; Optical imaging; Radiology; Biomedical engineering; Medicine; Cancer; Optics; In vivo; Physics; Internal medicine; Biology; Telecommunications; Fluorescence","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":[0.000211015,0.0001830137,0.0001668716,0.0003588807,0.00008162898,0.00009072106,0.0001357885,0.00007605357,0.00001895207],"category_scores_gemma":[0.00005348795,0.0001856296,0.00005872304,0.001097793,0.0001460849,0.0002212435,0.00002621402,0.0001402427,0.00001501874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005068606,"about_ca_system_score_gemma":0.00002132691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002130292,"about_ca_topic_score_gemma":0.0005621772,"domain_scores_codex":[0.9987598,0.00001488963,0.0002809857,0.0003641638,0.0001331134,0.0004470557],"domain_scores_gemma":[0.9993482,0.0001890711,0.00002770277,0.0002390922,0.00004524605,0.0001506713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001190509,0.00009634732,0.1071576,0.0005680377,0.0001292745,0.00001581442,0.0005417989,0.003438554,0.4066648,0.00186221,0.0008244778,0.478582],"study_design_scores_gemma":[0.0009879229,0.00004394224,0.2799374,0.0001131493,0.0000298558,0.000004531619,0.0002327719,0.6542858,0.06216807,0.0009603553,0.0007440061,0.0004920944],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9146379,0.0002715202,0.07644507,0.0007385589,0.0002553438,0.002917991,0.00008773298,0.002294065,0.002351795],"genre_scores_gemma":[0.9920585,0.00003717496,0.006476946,0.00002343959,0.00002196032,0.001321082,0.000009523354,0.0000313306,0.00002011025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6508473,"threshold_uncertainty_score":0.7569755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02311314503472478,"score_gpt":0.281267398893314,"score_spread":0.2581542538585893,"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."}}