{"id":"W2116196100","doi":"10.2460/ajvr.2002.63.175","title":"Effects of adenosine pretreatment on detection of free radicals in ischemic and reperfused canine gracilis muscle flaps by use of spin-trapping electron paramagnetic resonance spectroscopy","year":2002,"lang":"en","type":"article","venue":"American Journal of Veterinary Research","topic":"Reconstructive Surgery and Microvascular Techniques","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"OVC Pet Trust; Natural Sciences and Engineering Research Council of Canada","keywords":"Electron paramagnetic resonance; Electron paramagnetic resonance spectroscopy; Trapping; Radical; Spin trapping; Adenosine; Chemistry; Spectroscopy; Gracilis muscle; Nuclear magnetic resonance; Materials science; Internal medicine; Medicine; Biology; Biochemistry; Physics","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":[0.0006915276,0.0001384386,0.0006815108,0.0005226278,0.00002771738,0.000006021175,0.0001168861,0.00005383383,0.00001788669],"category_scores_gemma":[0.0004454242,0.0001191098,0.0001247623,0.0005880767,0.0007295451,0.0001088202,0.00003942837,0.000473388,1.653282e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00014008,"about_ca_system_score_gemma":0.00005366527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003586416,"about_ca_topic_score_gemma":0.000004153671,"domain_scores_codex":[0.998004,0.0004604409,0.0005819252,0.0002077231,0.0004620096,0.0002839652],"domain_scores_gemma":[0.9985545,0.0004480014,0.0003857323,0.0002964777,0.0002070968,0.0001082203],"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":[0.00188476,0.0004426957,0.002117665,0.0002254078,0.00007487862,0.0001414436,0.000158994,7.430801e-7,0.9318468,0.000001245424,0.0001371001,0.0629683],"study_design_scores_gemma":[0.001352576,0.0318252,0.02293767,0.001279098,0.00003496596,0.0004935511,0.00008461246,0.00003124644,0.9414719,0.00001032894,0.0004046195,0.00007421825],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993636,0.005763897,0.00006629288,0.00009172314,0.00001444144,0.0003802142,0.000006919545,0.000005380496,0.00003516051],"genre_scores_gemma":[0.9928226,0.005388896,0.001705995,0.000008097895,0.00001761228,0.00001076823,0.000001030816,0.00001689006,0.00002805859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06289408,"threshold_uncertainty_score":0.4857159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03393008982175231,"score_gpt":0.3253046320463979,"score_spread":0.2913745422246455,"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."}}