{"id":"W2232521377","doi":"10.3109/0284186x.2015.1067718","title":"Development of a method for functional aspect identification in parotid using dynamic contrast-enhanced magnetic resonance imaging and concurrent stimulation","year":2015,"lang":"en","type":"letter","venue":"Acta Oncologica","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"","keywords":"Medicine; Magnetic resonance imaging; Dynamic contrast; Dynamic contrast-enhanced MRI; Stimulation; Nuclear magnetic resonance; Contrast (vision); Functional magnetic resonance imaging; Functional imaging; Nuclear medicine; Radiology; Internal medicine; Artificial intelligence; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008766939,0.0002657842,0.0006812029,0.0002381193,0.00006042078,0.00002221236,0.0001001628,0.0003330857,0.00007789113],"category_scores_gemma":[0.0003419058,0.0002485774,0.00006816789,0.0001899524,0.00009051588,0.00008331084,0.00005396038,0.0004981079,0.000001622279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001377402,"about_ca_system_score_gemma":0.0007420819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002045228,"about_ca_topic_score_gemma":0.0000424496,"domain_scores_codex":[0.9977561,0.0001451095,0.000795579,0.0005891955,0.0004155372,0.0002984579],"domain_scores_gemma":[0.9980003,0.0007825514,0.0005454065,0.0002242823,0.0003913206,0.00005615695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000977137,0.0005361534,0.01054204,0.001814716,0.0001340342,0.00006448456,0.001283985,0.0002390127,0.07828447,0.0000245392,0.3035472,0.6025522],"study_design_scores_gemma":[0.01090757,0.0008391212,0.3308038,0.002233411,0.0008275196,0.00009035914,0.0002307817,0.07410016,0.006106631,0.0007866258,0.5720971,0.0009769853],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1970634,0.02208382,0.3762286,0.3794223,0.004574775,0.01889718,0.0005502893,0.0002776757,0.0009019113],"genre_scores_gemma":[0.6963364,0.0004692777,0.2622778,0.0362413,0.0009809748,0.001839784,0.00142694,0.0001001277,0.0003273989],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6015752,"threshold_uncertainty_score":0.9999967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07530444516070907,"score_gpt":0.3761737137534248,"score_spread":0.3008692685927158,"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."}}