{"id":"W3157410705","doi":"10.1002/nbm.4532","title":"Cardiac metabolic imaging using hyperpolarized [1‐ <sup>13</sup> C]lactate as a substrate","year":2021,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced NMR Techniques and Applications","field":"Chemistry","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Substrate (aquarium); Bicarbonate; Chemistry; In vivo; Hyperpolarization (physics); Metabolism; Biochemistry; Nuclear magnetic resonance spectroscopy; Biology; Stereochemistry","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":[0.0001861998,0.0002393212,0.0004607364,0.0001359723,0.0001047025,0.0000308586,0.0001946021,0.0001062912,0.0005578377],"category_scores_gemma":[0.00007896794,0.0002302897,0.0001112235,0.0007799283,0.0001507319,0.0001243717,0.00009291392,0.0003434172,0.00002800984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009049762,"about_ca_system_score_gemma":0.0001260157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004556707,"about_ca_topic_score_gemma":0.000006947063,"domain_scores_codex":[0.9983717,0.00002746587,0.0004359382,0.0004723882,0.0002627767,0.0004297398],"domain_scores_gemma":[0.9989989,0.00007332657,0.0001139925,0.000556958,0.0001111886,0.0001456216],"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":[0.00001944188,0.00008825386,0.006261144,0.00005765439,0.00003796904,0.0001323627,0.0002404088,0.000120768,0.9837083,0.0007168744,0.0001408506,0.008476009],"study_design_scores_gemma":[0.003734606,0.0000225918,0.002214231,0.0005870064,0.0003329873,0.0003549005,0.003194914,0.03080378,0.6806634,0.008000244,0.2690233,0.001068078],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9791467,0.005742213,0.002084841,0.001268523,0.0000358251,0.0001626568,0.0000774219,0.0002722277,0.01120964],"genre_scores_gemma":[0.9853697,0.0008652926,0.01165218,0.000423478,0.0003780634,0.00006994294,0.0002031005,0.00005819337,0.0009799891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3030449,"threshold_uncertainty_score":0.9390942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01686193490119431,"score_gpt":0.3039219870543686,"score_spread":0.2870600521531743,"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."}}