{"id":"W2322483761","doi":"10.1021/pr401056c","title":"Identification of Hypoxia-Regulated Proteins Using MALDI-Mass Spectrometry Imaging Combined with Quantitative Proteomics","year":2014,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Cancer Research","funders":"Breast Cancer Campaign; Association for International Cancer Research; Cancer Research UK","keywords":"Proteomics; Mass spectrometry; Mass spectrometry imaging; Quantitative proteomics; Hypoxia (environmental); Chemistry; Tandem mass tag; Chromatography; MALDI imaging; Posttranslational modification; Computational biology; Matrix-assisted laser desorption/ionization; Biology; Biochemistry; Oxygen; Enzyme","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":[0.001497893,0.001121027,0.0007280951,0.001705481,0.0004797065,0.0008048207,0.0008331351,0.0006260041,0.001217572],"category_scores_gemma":[0.001398436,0.0004105025,0.0005113634,0.001178905,0.0004591269,0.0009732131,0.0006387876,0.0008437101,0.0007743809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004303281,"about_ca_system_score_gemma":0.0003536092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007045631,"about_ca_topic_score_gemma":0.001064281,"domain_scores_codex":[0.9991415,0.0001498353,0.00005331661,0.000213628,0.0003758334,0.00006591619],"domain_scores_gemma":[0.9992115,0.0003156086,0.0001561856,0.00005916135,0.0002017829,0.00005567127],"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":[0.0000616793,0.00002612702,0.0006489168,0.0001242792,0.0000241249,0.0000353651,0.000027789,0.0002117469,0.9913282,0.0001287608,0.000116798,0.007266159],"study_design_scores_gemma":[0.00001249365,0.0001505367,0.008391971,0.00001764456,0.00004759573,0.0007586681,0.00005749898,0.01842474,0.9693636,0.0004573064,0.002277108,0.00004081361],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.390309,0.006967292,0.5934584,0.0007257336,0.0001296372,0.0003485049,0.002651206,0.002491315,0.00291898],"genre_scores_gemma":[0.3952197,0.005244859,0.5939788,0.0003569889,0.0001107197,0.000530557,0.001902151,0.0003119702,0.002344248],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001705481,"threshold_uncertainty_score":0.007921696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04127791799162246,"score_gpt":0.3547437521792515,"score_spread":0.3134658341876291,"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."}}