{"id":"W2990973034","doi":"10.1177/0271678x20905433","title":"Guidelines for the content and format of PET brain data in publications and archives: A consensus paper","year":2020,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Montreal Neurological Institute and Hospital; Canadian Sport Centre Pacific","funders":"National Center for Advancing Translational Sciences; National Institute of Mental Health; National Institutes of Health; Lundbeckfonden; Wellcome Trust","keywords":"Neuroimaging; Data sharing; Computer science; Data science; Data set; Preprocessor; Sample (material); Set (abstract data type); Multidisciplinary approach; Positron emission tomography; Statistical power; Data mining; Medical physics; Artificial intelligence; Information retrieval; Psychology; Medicine; Nuclear medicine; Statistics; Political science","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3351741,0.002530052,0.006034875,0.03502377,0.005390214,0.01963724,0.01615446,0.02032862,0.02080654],"category_scores_gemma":[0.4726727,0.004974309,0.0107791,0.02668471,0.007737867,0.01677945,0.01419404,0.01708872,0.03277108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006974933,"about_ca_system_score_gemma":0.04989629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007268986,"about_ca_topic_score_gemma":0.006949384,"domain_scores_codex":[0.6687089,0.1114625,0.1592861,0.007711871,0.04709023,0.005740459],"domain_scores_gemma":[0.3444928,0.2548325,0.05589702,0.06670893,0.2656061,0.0124627],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004172355,0.0003690822,0.001792208,0.02143457,0.000304091,0.0008446508,0.003288266,0.001517709,0.002596963,0.02460564,0.6501024,0.2927271],"study_design_scores_gemma":[0.0003344287,0.0001185001,0.002730767,0.04428605,0.0002063591,0.0005551875,0.001416329,0.0005408401,0.001413026,0.01511309,0.933029,0.0002563812],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006297567,0.0433903,0.3365552,0.3055241,0.05054981,0.1087581,0.05765603,0.01102688,0.08024216],"genre_scores_gemma":[0.01363722,0.03919076,0.6731891,0.06153814,0.008025989,0.1161683,0.04898888,0.004027331,0.03523421],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6648259,"threshold_uncertainty_score":0.8198487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1563990963508771,"score_gpt":0.3632717507611553,"score_spread":0.2068726544102782,"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."}}