{"id":"W4311599567","doi":"10.1109/ipc53466.2022.9975553","title":"System-agnostic 3D volume registration for motion-free contrast-enhanced optical coherence tomography retinal image","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Photonics Conference (IPC)","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Optical coherence tomography; Computer vision; Image registration; Contrast (vision); Retinal; Artificial intelligence; Volume (thermodynamics); Computer science; Coherence (philosophical gambling strategy); Optics; Image (mathematics); Physics; Ophthalmology; Medicine","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009294427,0.0003563607,0.0007150286,0.0002569518,0.0005651111,0.0001690954,0.0005321463,0.00009939368,0.0009470395],"category_scores_gemma":[0.0006617176,0.0003703329,0.0003949382,0.0006718034,0.0002667298,0.000165519,0.0001175119,0.0006954853,0.00003612044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002836784,"about_ca_system_score_gemma":0.0004403879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001819465,"about_ca_topic_score_gemma":0.00003883282,"domain_scores_codex":[0.9967064,0.0001742881,0.0007272531,0.0008373694,0.0009372964,0.0006174561],"domain_scores_gemma":[0.9974122,0.0002895351,0.0003826463,0.0009680614,0.0006637843,0.000283778],"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":[0.002870549,0.001559975,0.005636696,0.00211346,0.0009785328,0.0005484699,0.00139199,0.001201256,0.9331432,0.01242979,0.02893475,0.00919134],"study_design_scores_gemma":[0.01076393,0.004695716,0.005003513,0.001038789,0.003490953,0.0009318918,0.007214291,0.8460037,0.1085417,0.002043315,0.008232661,0.002039555],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6319501,0.0006136047,0.3292605,0.004804045,0.001583997,0.003727889,0.0009134911,0.0007039708,0.02644244],"genre_scores_gemma":[0.9867069,0.00004403656,0.008712139,0.0002610899,0.0001210173,0.0009448091,0.0003475212,0.00004771185,0.002814773],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8448024,"threshold_uncertainty_score":0.9999662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01592805904964123,"score_gpt":0.2621791386714388,"score_spread":0.2462510796217975,"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."}}