{"id":"W4379741083","doi":"10.1002/jbm4.10776","title":"Osteoclast <scp>microRNA</scp> Profiling in Rheumatoid Arthritis to Capture the Erosive Factor","year":2023,"lang":"en","type":"article","venue":"JBMR Plus","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centre Hospitalier Universitaire de Sherbrooke","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Pfizer Canada; Pfizer","keywords":"Osteoclast; Rheumatoid arthritis; Peripheral blood mononuclear cell; Medicine; microRNA; Immunology; Internal medicine; Biology; Gene; In vitro; Genetics; Receptor","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":[0.0002459483,0.0002105372,0.0001945953,0.000141478,0.0001241326,0.00006753867,0.0003933678,0.0002714236,0.00001648407],"category_scores_gemma":[0.0004887987,0.0001809383,0.0001077447,0.0005747373,0.00005704507,0.000004674199,0.000396281,0.000372288,0.0002856792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009895,"about_ca_system_score_gemma":0.0002755962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001278974,"about_ca_topic_score_gemma":0.0007610387,"domain_scores_codex":[0.9982046,0.0001012271,0.0002411311,0.0005129126,0.0003165957,0.0006234595],"domain_scores_gemma":[0.9991347,0.000048986,0.00005709897,0.0005037683,0.0001092149,0.0001462486],"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":[0.00002528428,0.00001234211,0.00008541349,0.0000139669,0.00003083724,0.00004904248,0.0005445693,0.001148938,0.989783,0.00008135362,0.006501665,0.001723597],"study_design_scores_gemma":[0.0009738936,0.0001669796,0.0008533744,0.00008334449,0.000002478607,0.00003846219,0.001153027,0.000256102,0.9541033,0.00006740198,0.04217166,0.0001300096],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934492,0.001686759,0.001526323,0.0006958545,0.0003754202,0.001022686,0.0001417784,0.00005730526,0.001044726],"genre_scores_gemma":[0.9955838,0.001180297,0.0001770761,0.0005253082,0.0001506456,0.0002469262,0.0001869909,0.0000680932,0.001880915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03567972,"threshold_uncertainty_score":0.7378448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01239417578315589,"score_gpt":0.2650890800024638,"score_spread":0.2526949042193079,"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."}}