{"id":"W3004353942","doi":"10.1101/2020.01.29.924530","title":"Cerebral grey matter density is associated with neuroreceptor and neurotransporter availability: A combined PET and MRI study","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Neuroscience and Neuropharmacology Research","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Ottawa Mental Health Centre; University of Ottawa","funders":"Päivikki ja Sakari Sohlbergin Säätiö; Varsinais-Suomen Rahasto; Suomen Kulttuurirahasto; Academy of Finland; Alfred Kordelinin Säätiö","keywords":"Grey matter; Voxel; Binding potential; Positron emission tomography; Nuclear medicine; Serotonin transporter; Raclopride; Nuclear magnetic resonance; Magnetic resonance imaging; Medicine; Physics; Internal medicine; Serotonin; Receptor; Radiology; Dopamine receptor D2; White matter","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003940717,0.0003472888,0.0004888996,0.0006419407,0.0001672887,0.0003709838,0.0001949261,0.0003822626,0.001839409],"category_scores_gemma":[0.0009245754,0.0003147958,0.0002287465,0.0003896652,0.0003689336,0.0002416863,0.0002726486,0.0001787477,0.0002947201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001609247,"about_ca_system_score_gemma":0.00009243805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001388408,"about_ca_topic_score_gemma":0.001874698,"domain_scores_codex":[0.9998341,0.00005143151,0.00001372535,0.00005409235,0.00002901079,0.00001775284],"domain_scores_gemma":[0.9996226,0.0001284099,0.0001243891,0.00004764111,0.00003656772,0.00004038554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004271071,0.0001673031,0.9407006,0.0001457759,0.001039954,0.002364703,0.0003262665,0.0006700831,0.03908185,0.0001474552,0.000188029,0.01089703],"study_design_scores_gemma":[0.00002400552,0.0003392845,0.9949747,0.000007349013,0.0001939424,0.002169653,0.00006873765,0.0006052959,0.001369637,0.00008364689,0.0001572708,0.000006339101],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988833,0.0004117985,0.0003242297,0.00001240354,0.00000178859,0.000007155241,0.00008916981,0.000004967231,0.0002652104],"genre_scores_gemma":[0.9995585,0.00007682414,0.0001377199,0.000004866172,0.000006851142,0.000004566491,0.00007895884,0.000001890598,0.0001299152],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001839409,"threshold_uncertainty_score":0.006153405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03210048135067037,"score_gpt":0.2578941385140408,"score_spread":0.2257936571633704,"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."}}