{"id":"W2612795351","doi":"10.1002/jbio.201600291","title":"Optical coherence elastography for strain dynamics measurements in laser correction of cornea shape","year":2017,"lang":"en","type":"article","venue":"Journal of Biophotonics","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"","keywords":"Optical coherence tomography; Optics; Cornea; Elastography; Laser; Materials science; Speckle pattern; Coherence (philosophical gambling strategy); Biomedical engineering; Computer science; Ultrasound; Physics; Acoustics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002535201,0.0002736669,0.0001581135,0.0004975024,0.0002022154,0.0002717784,0.0002294835,0.0002977503,0.001205937],"category_scores_gemma":[0.00064564,0.0001640543,0.00009374697,0.0004524552,0.0002425606,0.0003439086,0.0002926577,0.0003744064,0.0002243627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001927361,"about_ca_system_score_gemma":0.0002919777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006710178,"about_ca_topic_score_gemma":0.001959906,"domain_scores_codex":[0.9998398,0.00004047715,0.000009142774,0.00002896451,0.00006626548,0.00001528371],"domain_scores_gemma":[0.9996589,0.000173847,0.00005192164,0.00004659818,0.00005509842,0.00001360553],"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":[0.00006649605,0.00002426015,0.001147936,0.00008427005,0.000005527015,0.00007265724,0.00004143605,0.001333444,0.9660376,0.0005652306,0.0001792266,0.03044198],"study_design_scores_gemma":[0.00001947015,0.0002610735,0.01235679,0.0000309688,0.00002810203,0.001217476,0.00007457074,0.06248527,0.917411,0.0009637557,0.005121166,0.00003030769],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4115281,0.002505481,0.5792795,0.0004565816,0.00007511381,0.0001766014,0.0006750419,0.0006583703,0.004645283],"genre_scores_gemma":[0.6247593,0.001607295,0.3713054,0.0001251248,0.00003037582,0.0001946283,0.0002496414,0.00008164855,0.001646623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001205937,"threshold_uncertainty_score":0.004034281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02785489353710222,"score_gpt":0.2693311089987188,"score_spread":0.2414762154616165,"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."}}