{"id":"W4319596620","doi":"10.1063/5.0132123.2","title":"10.1063/5.0132123.2","year":2023,"lang":"en","type":"dataset","venue":"Default Digital Object Group","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Multi-mode optical fiber; Single shot; Frame rate; Reflection (computer programming); Optics; Computer science; Digital micromirror device; Computer vision; Artificial intelligence; Endoscope; Channel (broadcasting); Optical fiber; Physics; Telecommunications","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":[0.00009079567,0.0006133651,0.0005214016,0.0004176043,0.0000872786,0.0005243783,0.0008530297,0.000527108,0.0007718628],"category_scores_gemma":[0.0001367749,0.0006453285,0.0003457908,0.001287389,0.0001321621,0.0003805505,0.0001862178,0.0007254558,0.1197401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001106336,"about_ca_system_score_gemma":0.00002887691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006252545,"about_ca_topic_score_gemma":0.0001044588,"domain_scores_codex":[0.9976897,0.00001327949,0.0005205919,0.0005746225,0.0004978973,0.000703934],"domain_scores_gemma":[0.9981246,0.0002912607,0.0000713183,0.001175152,0.00006494601,0.0002727289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000004861776,0.00005376932,0.000001506769,0.0001729934,0.0001223752,0.00003451696,0.000003570565,0.0001155944,0.000004921403,0.00003428512,0.9961556,0.003296005],"study_design_scores_gemma":[0.0001559745,0.00008323424,0.00008462767,0.00007316055,0.00006601559,0.00001122513,0.0000124996,0.0002820407,0.000006812809,0.0004149868,0.9980941,0.0007153233],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004897868,0.000172439,0.00009972659,0.00001594774,0.0004053101,0.0004823551,0.9797805,0.001937119,0.01705764],"genre_scores_gemma":[0.000583322,0.00008784096,0.00005602844,0.00002522339,0.0003381717,0.0004559323,0.9960664,0.0001587529,0.002228318],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1189683,"threshold_uncertainty_score":0.9995998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00996180619286251,"score_gpt":0.2263696071014733,"score_spread":0.2164078009086108,"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."}}