{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007617766,0.00008539244,0.0001353168,0.00002233164,0.00002895959,0.00001329984,0.0003753002,0.00002517845,0.0001799692],"category_scores_gemma":[0.0001290432,0.00008469506,0.00001011913,0.0001964536,0.00004981814,0.0001982296,0.0004031712,0.0002069107,0.00006103073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001641098,"about_ca_system_score_gemma":0.00003629416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001406472,"about_ca_topic_score_gemma":0.00001112687,"domain_scores_codex":[0.9991208,0.00001085461,0.0001847308,0.0004027755,0.0001172226,0.0001636142],"domain_scores_gemma":[0.9986904,0.00002520931,0.0000289748,0.00112291,0.0000133499,0.0001191848],"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":[0.00006113381,0.00007863109,0.006284171,0.00003147217,9.28611e-7,0.0001399898,0.00002792667,0.000003132843,0.001522374,0.0009226337,0.8431029,0.1478247],"study_design_scores_gemma":[0.0004465034,0.00003125911,0.01270835,0.00004564234,0.00001229875,0.00002164851,0.00001212258,0.01019904,0.0002744521,0.0001288902,0.9760303,0.00008942438],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005961618,0.05813839,0.5476219,0.1924547,0.0002254853,0.008704152,0.1618572,0.002124172,0.02291244],"genre_scores_gemma":[0.05904902,0.003500806,0.6521571,0.06959824,0.0009520071,0.0004479391,0.2135606,0.0001584037,0.0005759543],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1477353,"threshold_uncertainty_score":0.3453764,"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."}}