{"id":"W2039722048","doi":"10.1117/1.2992129","title":"Assessment of early demineralization in teeth using the signal attenuation in optical coherence tomography images","year":2008,"lang":"en","type":"article","venue":"Journal of Biomedical Optics","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; National Research Council Institute for Biodiagnostics","funders":"National Institute of Dental and Craniofacial Research; Canadian Institutes of Health Research; Dalhousie University","keywords":"Demineralization; Optical coherence tomography; Enamel paint; Attenuation; Materials science; Molar; Attenuation coefficient; Dentistry; Optics; Biomedical engineering; Medicine; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005391601,0.0003694209,0.0002475643,0.00107111,0.0001403636,0.0002947913,0.000131936,0.0004523049,0.0006159666],"category_scores_gemma":[0.002571979,0.0002655595,0.00009865194,0.0002726844,0.0003230232,0.0002745701,0.0002828314,0.0001710294,0.0001844039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001026937,"about_ca_system_score_gemma":0.0001165037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006995851,"about_ca_topic_score_gemma":0.001521971,"domain_scores_codex":[0.9997402,0.00007105286,0.00001760501,0.00005003534,0.00009120645,0.00002996987],"domain_scores_gemma":[0.9991079,0.0003715647,0.0002233583,0.0000431452,0.0002001186,0.00005401457],"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":[0.00135253,0.0001647139,0.2829861,0.0002467043,0.0001262691,0.0003451823,0.0005285307,0.0004661728,0.6599516,0.00009124534,0.0001440863,0.05359691],"study_design_scores_gemma":[0.00002388881,0.001004874,0.8873174,0.00001813499,0.0001356011,0.001920881,0.0002424016,0.00337987,0.1051088,0.0001773916,0.0006490925,0.00002169203],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945275,0.0005088948,0.004563268,0.00001479364,0.000002068276,0.00002500822,0.0000347996,0.00002734285,0.0002962291],"genre_scores_gemma":[0.9935267,0.0003770489,0.005762557,0.00001448682,0.000006854071,0.00001809317,0.00005560506,0.000005372106,0.0002332946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00107111,"threshold_uncertainty_score":0.002851367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02339704398623881,"score_gpt":0.2891026427657423,"score_spread":0.2657055987795034,"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."}}