{"id":"W2898055864","doi":"10.1364/boe.9.005678","title":"Depth-multiplexed optical coherence tomography dual-beam manually-actuated distortion-corrected imaging (DMDI) with a micromotor catheter","year":2018,"lang":"en","type":"article","venue":"Biomedical Optics Express","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Occupational Cancer Research Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Optical coherence tomography; Optics; Imaging phantom; Multiplexing; Computer science; Distortion (music); Medical imaging; Physics; Bandwidth (computing); Artificial intelligence; Telecommunications","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":[0.0001936435,0.0005334384,0.0004594912,0.0003510256,0.0002202586,0.0002288693,0.0006299215,0.0002847348,0.0002292403],"category_scores_gemma":[0.000107627,0.0004636488,0.0001731231,0.001305527,0.001703129,0.0003172298,0.0001474184,0.0005457027,0.0001922008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001005999,"about_ca_system_score_gemma":0.0000673114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002745415,"about_ca_topic_score_gemma":0.00002717853,"domain_scores_codex":[0.9968922,0.00004307316,0.0006635748,0.0007060288,0.0007476416,0.0009474652],"domain_scores_gemma":[0.9976482,0.0002230705,0.00009703008,0.000852652,0.0003966692,0.0007823466],"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":[0.0003424837,0.001985346,0.004991719,0.0002786968,0.0006265183,0.000188425,0.001578932,0.0001541237,0.964588,0.001111878,0.008714423,0.01543943],"study_design_scores_gemma":[0.01279258,0.004221474,0.07286727,0.00190386,0.001391573,0.0007796801,0.001213121,0.2405859,0.5851231,0.001277083,0.06823125,0.00961315],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8511522,0.0002200608,0.1369553,0.0002679578,0.000852073,0.001385316,0.0001928351,0.002165749,0.006808515],"genre_scores_gemma":[0.9504321,0.00001612281,0.0483526,0.00009926087,0.000355916,0.0004060708,0.0001592391,0.0001086334,0.00007004909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.379465,"threshold_uncertainty_score":0.9997815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008210464491235305,"score_gpt":0.22484473632812,"score_spread":0.2166342718368847,"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."}}