{"id":"W4211150022","doi":"10.3389/fdmed.2022.814603","title":"Application of Proteomics in Apical Periodontitis","year":2022,"lang":"en","type":"article","venue":"Frontiers in Dental Medicine","topic":"Endodontics and Root Canal Treatments","field":"Dentistry","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sinai Health System; Mount Sinai Hospital; University of Toronto","funders":"Faculty of Dentistry, University of Toronto; Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Periodontitis; Proteomics; Biomarker; Biomarker discovery; Pathology; Root canal; Metabolomics; Computational biology; Bioinformatics; Medicine; Quantitative proteomics; Biology; Dentistry; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002001971,0.00009335606,0.0002867606,0.0002458154,0.00004255629,0.000002936546,0.0002012222,0.00003855972,0.0001465884],"category_scores_gemma":[0.0000414115,0.00008898025,0.00003742141,0.000366704,0.00009455981,0.0000368225,0.0001054223,0.0002108386,0.000004391215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003315318,"about_ca_system_score_gemma":0.00002031327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009115897,"about_ca_topic_score_gemma":0.0005855299,"domain_scores_codex":[0.9988664,0.00006451983,0.0003502152,0.0002073094,0.0003502254,0.0001613598],"domain_scores_gemma":[0.9996412,0.00001583915,0.00009951971,0.0001850653,0.00001238517,0.00004603339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001011307,0.000188781,0.99119,0.00002643066,0.00001848172,0.0002040006,0.0002513804,0.00008125524,0.001152304,0.0002857508,0.003331888,0.003168571],"study_design_scores_gemma":[0.005941658,0.000420037,0.9757981,0.00008802999,0.00003627289,0.0001318673,0.003797005,0.005232273,0.0009740448,0.001343713,0.006040436,0.0001965856],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893239,0.001072349,0.00595424,0.0001962918,0.001534997,0.0005343807,0.00003203647,0.00001203847,0.001339749],"genre_scores_gemma":[0.9953562,0.00002937552,0.003616397,0.00005804348,0.000057753,0.0001775309,0.00006175709,0.00001418633,0.0006287684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01539195,"threshold_uncertainty_score":0.3628509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00814372934532383,"score_gpt":0.2576799822296211,"score_spread":0.2495362528842972,"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."}}