{"id":"W2167585586","doi":"10.2967/jnumed.110.076612","title":"The Temporal Dynamics of Poststroke Neuroinflammation: A Longitudinal Diffusion Tensor Imaging–Guided PET Study with <sup>11</sup>C-PK11195 in Acute Subcortical Stroke","year":2010,"lang":"en","type":"article","venue":"Journal of Nuclear Medicine","topic":"Neuroinflammation and Neurodegeneration Mechanisms","field":"Neuroscience","cited_by":169,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Jewish General Hospital","funders":"Canadian Institutes of Health Research; Jewish General Hospital","keywords":"Diffusion MRI; Fractional anisotropy; Stroke (engine); Medicine; Neuroinflammation; Pyramidal tracts; Lesion; Fiber tract; Nuclear medicine; In vivo; Effective diffusion coefficient; Pathology; Magnetic resonance imaging; Internal medicine; Radiology; Inflammation; Anatomy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003278871,0.0003592854,0.0003731861,0.0003606622,0.0003989152,0.0003686712,0.0001983025,0.0004817831,0.0006696213],"category_scores_gemma":[0.000661409,0.0002607464,0.0001855832,0.0002677403,0.0004674076,0.0004077177,0.0002040904,0.000396979,0.0003790536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003231375,"about_ca_system_score_gemma":0.0002055765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001382189,"about_ca_topic_score_gemma":0.00115107,"domain_scores_codex":[0.9999073,0.00001775519,0.00001172401,0.00002604272,0.00001322974,0.0000240001],"domain_scores_gemma":[0.9995401,0.00005550442,0.000209617,0.00003687454,0.00005643885,0.0001014535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01037461,0.001560941,0.8588597,0.0001023571,0.0001895034,0.007586605,0.001022835,0.0006808239,0.1014476,0.00007669996,0.0002802062,0.0178182],"study_design_scores_gemma":[0.0001496066,0.004282049,0.9798176,0.00001229885,0.00008637759,0.007430894,0.0001781607,0.0009763502,0.006608248,0.00006935777,0.0003651169,0.00002405253],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995626,0.00009701784,0.0001610877,0.00001926519,0.000001156188,0.000007981705,0.00003294934,0.000004072852,0.0001138801],"genre_scores_gemma":[0.999544,0.00007365073,0.0001366898,0.00001885815,0.000008666205,0.00001541002,0.0001020167,0.000001829377,0.00009884396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001382189,"threshold_uncertainty_score":0.002748251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01633553842156863,"score_gpt":0.2687406332094659,"score_spread":0.2524050947878972,"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."}}