{"id":"W4410361241","doi":"10.3390/ma18102290","title":"Utilizing T1- and T2-Specific Contrast Agents as “Two Colors” MRI Correlation","year":2025,"lang":"en","type":"article","venue":"Materials","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Calgary; University of Victoria","funders":"","keywords":"Contrast (vision); Correlation; Materials science; Nuclear magnetic resonance; Artificial intelligence; Mathematics; Computer science; Physics; Geometry","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":[],"consensus_categories":[],"category_scores_codex":[0.001474164,0.0008685655,0.0004720992,0.0007144701,0.000304536,0.0006994335,0.0006910935,0.001030342,0.0005769771],"category_scores_gemma":[0.001836819,0.0005432785,0.0003770208,0.0004997398,0.0008544889,0.001158174,0.0007056752,0.0009639265,0.0003664409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003820717,"about_ca_system_score_gemma":0.0005734111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005968815,"about_ca_topic_score_gemma":0.0009937343,"domain_scores_codex":[0.9992429,0.0002481605,0.00003179903,0.0002358154,0.0001744874,0.00006683209],"domain_scores_gemma":[0.9992855,0.0002962151,0.0001732928,0.00008112239,0.0001067316,0.00005715392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001335562,0.00003718051,0.0005386148,0.0001374884,0.00002706036,0.0001355456,0.00005154387,0.0008173022,0.9833969,0.001225978,0.0002154994,0.01328332],"study_design_scores_gemma":[0.00002103389,0.0002966838,0.001181458,0.00001415656,0.00005227953,0.000511148,0.00001675852,0.01531116,0.9781021,0.0003966605,0.004053088,0.00004351599],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3497286,0.005990494,0.6360905,0.0006663427,0.0002219045,0.0003375268,0.0001660157,0.001284403,0.005514327],"genre_scores_gemma":[0.5430673,0.002090166,0.451183,0.0004479134,0.00007536083,0.0002794388,0.0002029903,0.0001431593,0.002510726],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001474164,"threshold_uncertainty_score":0.007796168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02257589018650661,"score_gpt":0.3465468627508469,"score_spread":0.3239709725643403,"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."}}