{"id":"W2340137604","doi":"10.1364/cancer.2016.jm3a.21","title":"Removal of limited dynamic range artifacts from swept-source optical coherence tomography images","year":2016,"lang":"en","type":"article","venue":"","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Optical coherence tomography; Computer science; Dynamic range; Coherence (philosophical gambling strategy); Tomography; Graphics processing unit; Computer vision; Point spread function; Optical tomography; Graphics; Optics; Artificial intelligence; Computer graphics (images); Physics; Parallel computing","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":[0.0003978591,0.0006045123,0.0004444392,0.000720474,0.0003051496,0.0006967424,0.0009652458,0.000622442,0.001174127],"category_scores_gemma":[0.001565348,0.0003358004,0.0003117355,0.0004338242,0.0003205185,0.0007212661,0.0005261475,0.0006592888,0.0006818401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002401865,"about_ca_system_score_gemma":0.0006161818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007073194,"about_ca_topic_score_gemma":0.001767873,"domain_scores_codex":[0.9997612,0.00002816531,0.00001729927,0.00003537333,0.0001377308,0.00002023258],"domain_scores_gemma":[0.9993187,0.0002722519,0.00008656021,0.0001012128,0.0001905757,0.00003063383],"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":[0.0001796153,0.00006283269,0.0008234911,0.0001671698,0.00005006727,0.0002976263,0.0001632799,0.008510385,0.5456138,0.001787025,0.00128601,0.4410586],"study_design_scores_gemma":[0.00007640986,0.0002669745,0.003048174,0.00003241116,0.00006123239,0.001588872,0.00004815729,0.3015079,0.6785337,0.002396416,0.01237721,0.0000626277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02094495,0.0001393556,0.9776875,0.0000677756,0.00002406955,0.00005367318,0.00002473056,0.0007717209,0.0002861747],"genre_scores_gemma":[0.03791064,0.0001312838,0.9610944,0.00003511755,0.00001474527,0.00006358906,0.00005471692,0.00009360278,0.0006019277],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001174127,"threshold_uncertainty_score":0.003927827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00911525778370896,"score_gpt":0.2162863348452311,"score_spread":0.2071710770615222,"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."}}