{"id":"W2106358463","doi":"10.3389/fgene.2013.00090","title":"Erratum: microRNA dysregulation in multiple sclerosis","year":2013,"lang":"en","type":"erratum","venue":"Frontiers in Genetics","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"microRNA; Multiple sclerosis; Computational biology; Biology; Neuroscience; Genetics; Gene; Immunology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0001825937,0.0004896742,0.000472459,0.0004117094,0.00005348254,0.00006769431,0.0004953636,0.001427591,0.00002874759],"category_scores_gemma":[0.0001032992,0.0005869997,0.0001662102,0.0003195901,0.0001496768,0.000007141021,0.0002174926,0.0004942922,0.00002355935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002319711,"about_ca_system_score_gemma":0.0003026984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006062516,"about_ca_topic_score_gemma":0.0003294424,"domain_scores_codex":[0.9974735,0.0001585023,0.0006636138,0.0008620034,0.0002814036,0.0005610044],"domain_scores_gemma":[0.9985728,0.000006866743,0.0003040512,0.0008647689,0.0001244594,0.0001270584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004737182,0.00009004027,0.01984401,0.0001069189,0.00005057456,0.000003512995,0.00004587926,0.0008557208,0.05827739,0.000001063022,0.9168394,0.003838152],"study_design_scores_gemma":[0.002456222,0.0001711202,0.2877172,0.0006243552,0.00009212301,0.000006337278,0.0001275303,0.01028727,0.02130771,0.0006147963,0.6749474,0.001647888],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7270971,0.1567633,0.01280216,0.0004675503,0.08571304,0.004943572,0.0005706609,0.0001020031,0.01154067],"genre_scores_gemma":[0.6311898,0.03280147,0.1035616,0.0009620528,0.009183979,0.0009514127,0.03159963,0.001109754,0.1886403],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2678732,"threshold_uncertainty_score":0.9998688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01580997274320282,"score_gpt":0.2169424760050038,"score_spread":0.2011325032618009,"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."}}