{"id":"W2042846944","doi":"10.1364/boe.3.002647","title":"Extended coherence length megahertz FDML and its application for anterior segment imaging","year":2012,"lang":"en","type":"article","venue":"Biomedical Optics Express","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"TeraXion (Canada)","funders":"FP7 Health; Deutsche Forschungsgemeinschaft; European Commission","keywords":"Optical coherence tomography; Optics; Laser; Coherence length; Human eye; Coherence (philosophical gambling strategy); Lens (geology); Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002159321,0.0001925172,0.0001970963,0.00008859585,0.00009051259,0.00004026861,0.0002208269,0.0001052356,0.00002588745],"category_scores_gemma":[0.0000459828,0.0001858297,0.00005400392,0.0002077013,0.0001345497,0.0002128909,0.00006662828,0.0001353941,0.00002290016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003833381,"about_ca_system_score_gemma":0.00001245617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002046179,"about_ca_topic_score_gemma":3.241003e-7,"domain_scores_codex":[0.9987271,0.00001370406,0.0003050168,0.0002393855,0.0002348258,0.0004799847],"domain_scores_gemma":[0.9990881,0.0001403665,0.00004352857,0.0002668239,0.00006445426,0.0003967235],"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":[0.00003117331,0.0005095171,0.0007625991,0.0005540141,0.0001155381,0.000001496172,0.0005960635,0.00003665145,0.8163689,0.0197199,0.001280418,0.1600237],"study_design_scores_gemma":[0.003358562,0.0002642438,0.01289192,0.0003671315,0.0003403733,0.00005402992,0.0006079832,0.7100198,0.1300414,0.003165994,0.1366899,0.002198642],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2200283,0.006787541,0.765443,0.0006547103,0.0006600506,0.002845882,0.0002385849,0.0009976703,0.002344306],"genre_scores_gemma":[0.9755275,0.0001317504,0.02294972,0.00005193869,0.000223866,0.001017817,0.00003344571,0.00003800612,0.000025955],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7554992,"threshold_uncertainty_score":0.7577915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01227348613526602,"score_gpt":0.257477966399382,"score_spread":0.245204480264116,"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."}}