{"id":"W3003742439","doi":"10.1016/j.dib.2020.105224","title":"Calgary Preschool magnetic resonance imaging (MRI) dataset","year":2020,"lang":"en","type":"article","venue":"Data in Brief","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Children's Hospital Research Institute","keywords":"Magnetic resonance imaging; Nuclear magnetic resonance; Functional magnetic resonance imaging; Computer science; Medicine; Physics; Radiology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001073182,0.002340838,0.001633234,0.004347721,0.001140856,0.001528824,0.004179623,0.001829833,0.02406348],"category_scores_gemma":[0.005099342,0.0004832043,0.0006762365,0.004955295,0.000455589,0.0007210355,0.002138404,0.001399405,0.01996879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002738228,"about_ca_system_score_gemma":0.003270258,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1534536,"about_ca_topic_score_gemma":0.2562828,"domain_scores_codex":[0.9990935,0.0001138885,0.0001087766,0.0002977953,0.0002503384,0.0001356795],"domain_scores_gemma":[0.9981812,0.0003259348,0.0001572496,0.0003520534,0.0007950823,0.0001884145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004467508,0.0001467882,0.01128792,0.001112942,0.000169075,0.0007374684,0.0001199997,0.0007171574,0.0008391318,0.0007648588,0.9525275,0.03113046],"study_design_scores_gemma":[0.000676816,0.0001605293,0.09844636,0.001264204,0.0002170009,0.001364985,0.0006571049,0.002642272,0.001628619,0.002216747,0.8905778,0.0001474728],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005789508,0.0007834989,0.0005804318,0.0002237751,0.00005934106,0.0001744505,0.9896514,0.0007746948,0.001962872],"genre_scores_gemma":[0.003711433,0.0002811881,0.001638569,0.0001016445,0.00001724037,0.0003773191,0.993073,0.00005944461,0.0007401653],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8465464,"threshold_uncertainty_score":0.3051207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03547979648695539,"score_gpt":0.330338233046259,"score_spread":0.2948584365593036,"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."}}