{"id":"W3011799086","doi":"10.1016/j.saa.2020.118267","title":"Combining surface-enhanced Raman scattering (SERS) of saliva and two-dimensional shear wave elastography (2D-SWE) of the parotid glands in the diagnosis of Sjögren's syndrome","year":2020,"lang":"en","type":"article","venue":"Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy","topic":"Salivary Gland Disorders and Functions","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii; European Regional Development Fund; Universitatea Babeș-Bolyai; Ontario Ministry of Research, Innovation and Science","keywords":"Chemistry; Elastography; Linear discriminant analysis; Principal component analysis; Saliva; Raman scattering; Raman spectroscopy; Analytical Chemistry (journal); Optics; Chromatography; Radiology; Ultrasound; Artificial intelligence; Biochemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001284817,0.0007373639,0.0006305877,0.001954033,0.0002366479,0.0006437822,0.0003697341,0.001122598,0.0002479101],"category_scores_gemma":[0.0013087,0.0004314336,0.0004246809,0.0007331487,0.0005243516,0.0005647186,0.0004838329,0.0006140679,0.0001615469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001308755,"about_ca_system_score_gemma":0.0001527484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003533431,"about_ca_topic_score_gemma":0.0005905967,"domain_scores_codex":[0.9992304,0.0002738331,0.0001069379,0.0001078872,0.0002202614,0.00006069649],"domain_scores_gemma":[0.9995161,0.0002226372,0.00006184759,0.00003142829,0.000106789,0.00006123364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003562622,0.0002974571,0.3999361,0.0003230637,0.0003148942,0.009419806,0.0005538072,0.00124328,0.4974602,0.000270545,0.0005503264,0.08606795],"study_design_scores_gemma":[0.0002522907,0.003255252,0.5588219,0.0001859227,0.001038559,0.07342909,0.001981195,0.04366583,0.3102856,0.002150423,0.004790508,0.0001435124],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858277,0.005883527,0.006053987,0.0003520033,0.000132583,0.00003179222,0.00007272586,0.0001069442,0.001538778],"genre_scores_gemma":[0.9922445,0.001522184,0.005711102,0.0001323451,0.00008735139,0.00001108053,0.00005683327,0.000007860021,0.0002267424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001954033,"threshold_uncertainty_score":0.00679487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01198968197866628,"score_gpt":0.2403968900433289,"score_spread":0.2284072080646626,"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."}}