{"id":"W2737355521","doi":"10.1002/jms.3957","title":"Myofiber metabolic type determination by mass spectrometry imaging","year":2017,"lang":"en","type":"article","venue":"Journal of Mass Spectrometry","topic":"Muscle metabolism and nutrition","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Generalitat de Catalunya; Canadian Institute for Advanced Research","keywords":"Chemistry; Glycolysis; Mass spectrometry; Myocyte; Fiber type; Mass spectrometry imaging; Matrix-assisted laser desorption/ionization; Oxidative phosphorylation; Biochemistry; Metabolism; Biophysics; Fiber; Chromatography; Cell biology; Desorption; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005127037,0.0006426341,0.0003691208,0.0008643154,0.0001867236,0.0005685876,0.0003688993,0.0005918305,0.0008870964],"category_scores_gemma":[0.0004525447,0.0002764392,0.0004073284,0.0004824078,0.0002384328,0.0004606007,0.0002630539,0.0003438555,0.000803428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002414346,"about_ca_system_score_gemma":0.0002004719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009828728,"about_ca_topic_score_gemma":0.001185152,"domain_scores_codex":[0.9998162,0.00001499625,0.00000840453,0.00009599762,0.0000465482,0.0000177592],"domain_scores_gemma":[0.9998159,0.00003265692,0.00005404527,0.00002626461,0.00005425644,0.00001699935],"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":[0.0002511662,0.00005321487,0.01465725,0.0001226835,0.00004402694,0.0001455594,0.00006133844,0.007709474,0.9421303,0.0005812236,0.0003614707,0.03388231],"study_design_scores_gemma":[0.00001621087,0.0003437837,0.07765809,0.00004235042,0.0001168948,0.0007033777,0.0001166655,0.3673982,0.547839,0.002157972,0.003529623,0.00007792957],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5429678,0.001617892,0.4491615,0.00009887059,0.00005375085,0.0001514537,0.001584522,0.00119076,0.003173459],"genre_scores_gemma":[0.8262619,0.001778827,0.1664076,0.00006911007,0.00002318012,0.0001916635,0.00168175,0.0001370691,0.00344877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009828728,"threshold_uncertainty_score":0.002967656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007807054850489557,"score_gpt":0.2621116619688548,"score_spread":0.2543046071183653,"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."}}