{"id":"W4391932769","doi":"10.1007/s13534-024-00353-8","title":"Distal planar rotary scanner for endoscopic optical coherence tomography","year":2024,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"BC Cancer Agency; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia","keywords":"Optical coherence tomography; Scanner; Planar; Tomography; Optics; Physics; Computer science; Computer graphics (images)","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":[0.0001156516,0.0002779778,0.0002227322,0.0003357,0.00004547097,0.0001084401,0.0002917876,0.0001425551,0.00006018823],"category_scores_gemma":[0.00003656652,0.0002677682,0.0001920663,0.0007827638,0.0001712479,0.0001301395,0.00002156803,0.0003388196,0.00005775444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006493454,"about_ca_system_score_gemma":0.0000189245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004782921,"about_ca_topic_score_gemma":8.0968e-7,"domain_scores_codex":[0.9984693,0.000005227231,0.0003045243,0.0003577237,0.0002922402,0.0005709853],"domain_scores_gemma":[0.9990923,0.0002840839,0.000008109118,0.0002606633,0.00001481166,0.0003400362],"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":[0.00002161777,0.0001542329,0.0002490336,0.002975695,0.0008217638,0.0001951974,0.0002476305,0.01455366,0.8349708,0.03323625,0.08450015,0.02807401],"study_design_scores_gemma":[0.001029576,0.0002791499,0.004337141,0.0008531507,0.0002445847,0.00005540129,0.00003420494,0.630443,0.01165795,0.0005166218,0.3488413,0.001707856],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1101308,0.001475165,0.8784328,0.002993162,0.001942301,0.0008393828,0.0002851169,0.003498585,0.0004027418],"genre_scores_gemma":[0.9715828,0.00001425979,0.02682539,0.0001743778,0.0005192923,0.0006443296,0.0001332317,0.00009121824,0.00001508654],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.861452,"threshold_uncertainty_score":0.9999775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006440255764899144,"score_gpt":0.2080601660795262,"score_spread":0.201619910314627,"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."}}