{"id":"W2528099920","doi":"10.1002/ana.24791","title":"Neuroinflammatory component of gray matter pathology in multiple sclerosis","year":2016,"lang":"en","type":"article","venue":"Annals of Neurology","topic":"Neuroinflammation and Neurodegeneration Mechanisms","field":"Neuroscience","cited_by":198,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Montreal Heart Institute","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; Multiple Sclerosis Society; Fondazione Italiana Sclerosi Multipla; National Multiple Sclerosis Society","keywords":"Translocator protein; Neuroinflammation; White matter; Multiple sclerosis; Pathology; Thalamus; Cortex (anatomy); Neurodegeneration; Lesion; Grey matter; Medicine; Microglia; Neuroscience; Magnetic resonance imaging; Psychology; Internal medicine; Inflammation; Radiology; 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":[],"consensus_categories":[],"category_scores_codex":[0.0002374566,0.0001858273,0.0003754304,0.0003858175,0.00004083778,0.000005301468,0.0003494518,0.0001064975,0.0002407854],"category_scores_gemma":[0.000478504,0.0001469864,0.0001129463,0.0002349261,0.0002978744,0.0001626807,0.0001281751,0.000146095,0.0001635751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002283426,"about_ca_system_score_gemma":0.00002356268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006222997,"about_ca_topic_score_gemma":0.00001584586,"domain_scores_codex":[0.9973836,0.0007601841,0.0007402232,0.0005282048,0.0002332707,0.0003545275],"domain_scores_gemma":[0.9982153,0.0007801442,0.0003791929,0.0004730381,0.00007142963,0.00008086274],"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":[0.0002221692,0.000118123,0.009736626,0.00001553325,0.000001173926,0.00007561712,0.00004787215,0.00007174734,0.9858642,0.002626375,0.0005437237,0.0006768508],"study_design_scores_gemma":[0.0007974129,0.0003470975,0.08032334,0.00001267688,0.00000200821,0.00006341554,0.000001278563,0.0001402179,0.91668,0.0007175123,0.0008062376,0.0001088453],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911472,0.000009874227,0.0002182204,0.007644522,0.0003934013,0.0002330431,0.00002383355,0.00004149914,0.0002883967],"genre_scores_gemma":[0.9909102,0.0001993044,0.00002905455,0.008713038,0.00002872467,0.00001811691,8.879518e-7,0.00002849816,0.00007215198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07058671,"threshold_uncertainty_score":0.5993932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1351890103344935,"score_gpt":0.2799888587058455,"score_spread":0.144799848371352,"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."}}