{"id":"W2136054697","doi":"10.4137/mri.s23555","title":"The Interface Between Iron Metabolism and Gene-Based Iron Contrast for MRI","year":2015,"lang":"en","type":"article","venue":"Magnetic Resonance Insights","topic":"Iron Metabolism and Disorders","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Cancer Care Ontario","keywords":"Magnetic resonance imaging; Context (archaeology); Gene expression; Molecular imaging; Cell biology; Cell; Nuclear magnetic resonance; Regulation of gene expression; Gene; Chemistry; Computational biology; Biophysics; Biology; Biochemistry; Genetics; Physics; In vivo; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002688296,0.0002336569,0.0003888319,0.00006237577,0.0001798546,0.00006727231,0.0001625853,0.0001152981,0.00001327715],"category_scores_gemma":[0.0001878402,0.0001487606,0.00007262944,0.0001217442,0.0002981374,0.0000711808,0.00004177685,0.0001511437,0.00002207213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000229183,"about_ca_system_score_gemma":0.0001516249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006507876,"about_ca_topic_score_gemma":0.00004761739,"domain_scores_codex":[0.9985292,0.00007759476,0.0003241787,0.0003631938,0.000319631,0.0003862113],"domain_scores_gemma":[0.9988621,0.0002303475,0.00008199841,0.0004246329,0.0001405281,0.000260382],"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":[0.004831652,0.0004316113,0.01803255,0.0005675099,0.00003694747,0.00004475155,0.005204617,0.00008623068,0.009651663,0.009420907,0.05329441,0.8983971],"study_design_scores_gemma":[0.007531272,0.0005649507,0.09256615,0.00004257691,0.0002258843,0.00000657956,0.0002881418,0.0005661636,0.005489896,0.001345743,0.8911228,0.0002498602],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.768671,0.2223799,0.002046546,0.00288188,0.0004075558,0.00119966,0.0000271463,0.00006035426,0.002325895],"genre_scores_gemma":[0.9910218,0.00115542,0.003009107,0.0007060093,0.0004801698,0.0001324845,0.00002455127,0.00004534962,0.003425123],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8981473,"threshold_uncertainty_score":0.6066281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02016059271915511,"score_gpt":0.2735300296314293,"score_spread":0.2533694369122742,"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."}}