{"id":"W4403214114","doi":"10.1021/acssensors.4c01604","title":"A Nitric Oxide-Sensing <i>T</i><sub>1</sub> Contrast Agent for In Vivo Molecular MR Imaging of Inflammatory Disease","year":2024,"lang":"en","type":"article","venue":"ACS Sensors","topic":"Electron Spin Resonance Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ted Rogers Centre for Heart Research; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science; University of Toronto; Canada Foundation for Innovation; Government of Ontario","keywords":"In vivo; Nitric oxide; Contrast (vision); Molecular imaging; Chemistry; Medicine; Nanotechnology; Biomedical engineering; Materials science; Nuclear magnetic resonance; Pathology; Computer science; Internal medicine; Biology; Physics; Artificial intelligence; Biotechnology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001955721,0.0003560202,0.0001642907,0.0001777199,0.0001882926,0.0002087652,0.0002470734,0.000556997,0.0007516641],"category_scores_gemma":[0.0002021225,0.0001497787,0.0001100458,0.00008590009,0.0002695971,0.000293233,0.0002152486,0.0004377632,0.000249944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002085032,"about_ca_system_score_gemma":0.0001480619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002680496,"about_ca_topic_score_gemma":0.0004487941,"domain_scores_codex":[0.9999442,0.00001740789,0.00000203716,0.0000139875,0.00001117808,0.00001115933],"domain_scores_gemma":[0.9999272,0.00002152061,0.00001947101,0.000004764715,0.000009227185,0.00001788206],"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":[0.00004155589,0.00001485538,0.00006381405,0.00005178802,0.000002687141,0.00005618963,0.000009144877,0.00009233516,0.9969751,0.0002964316,0.0001068513,0.002289175],"study_design_scores_gemma":[0.000009030998,0.0002472514,0.0003330545,0.000008065251,0.00001265129,0.0003064256,0.000008541941,0.00141368,0.9934048,0.00008314062,0.004167554,0.000005774075],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.794298,0.0151534,0.1792743,0.001736561,0.000312298,0.0002776912,0.0001914839,0.0004980908,0.008258229],"genre_scores_gemma":[0.8812563,0.004596904,0.1065347,0.00043596,0.00007426627,0.0001051461,0.000100814,0.00005426631,0.006841621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007516641,"threshold_uncertainty_score":0.002514601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005011989794555478,"score_gpt":0.2328201287704396,"score_spread":0.2278081389758841,"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."}}