{"id":"W4294938536","doi":"10.3389/fnins.2022.943512","title":"Four decades of mapping and quantifying neuroreceptors at work in vivo by positron emission tomography","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Statens Naturvidenskabelige Forskningsrad; National Institutes of Health; National Science Foundation","keywords":"Neurochemical; Positron emission tomography; Neuroscience; Computer science; Neuroimaging; Medical physics; Artificial intelligence; Data science; Cognitive science; Psychology; Medicine","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":[0.005634415,0.001276504,0.001375712,0.002987957,0.0007781446,0.003020573,0.001817715,0.003806694,0.00186739],"category_scores_gemma":[0.006163846,0.001089265,0.001292424,0.002238213,0.006631001,0.005912358,0.002850381,0.006190238,0.001307884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003059109,"about_ca_system_score_gemma":0.001872851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003332058,"about_ca_topic_score_gemma":0.002342909,"domain_scores_codex":[0.9979216,0.0006130153,0.00018656,0.0004780706,0.0006915783,0.0001092467],"domain_scores_gemma":[0.9957603,0.002675069,0.0002803689,0.0004660951,0.0006981306,0.0001200653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005692602,0.0003134672,0.003693118,0.004867454,0.0002937109,0.0003797604,0.001417899,0.01245271,0.06644469,0.2337928,0.01662236,0.6591527],"study_design_scores_gemma":[0.00006443942,0.001210644,0.004936209,0.002971599,0.0002599711,0.002550529,0.0008657972,0.01095542,0.0744952,0.1331484,0.7680682,0.0004736122],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.01273715,0.5477285,0.3987524,0.01864369,0.002066665,0.0001635016,0.0004040886,0.0004423105,0.01906174],"genre_scores_gemma":[0.1011156,0.6536281,0.2187053,0.006097749,0.003638111,0.0004642939,0.0005431714,0.0003915941,0.01541611],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005634415,"threshold_uncertainty_score":0.02979797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03096937362849581,"score_gpt":0.2855145833204794,"score_spread":0.2545452096919836,"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."}}