{"id":"W3123409937","doi":"10.1021/acs.jproteome.0c00629","title":"MicroPOTS Analysis of Barrett’s Esophageal Cell Line Models Identifies Proteomic Changes after Physiologic and Radiation Stress","year":2021,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome British Columbia; University of Victoria","funders":"Pacific Northwest National Laboratory; Office of Science; Ministerstvo Zdravotnictví Ceské Republiky; Biological and Environmental Research; Fundacja na rzecz Nauki Polskiej; European Commission; European Regional Development Fund; Genome British Columbia; Genome Canada; Infrastruktura PL-Grid; U.S. Department of Energy","keywords":"Proteomics; S100A9; Cell culture; Computational biology; Population; Biology; Chemistry; Molecular biology; Biochemistry; Medicine; Immunology; Inflammation; Genetics","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":[0.0007160676,0.0001356236,0.0004282482,0.0004468129,0.0001092479,0.00006606208,0.0002678782,0.0001482859,0.0002332346],"category_scores_gemma":[0.0001000796,0.000117014,0.000159107,0.0007928833,0.0001580086,0.0001931363,0.0001942966,0.0006236092,0.000001295714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009399178,"about_ca_system_score_gemma":0.0001408976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000199599,"about_ca_topic_score_gemma":0.00001028221,"domain_scores_codex":[0.998339,0.0001141894,0.0004913189,0.0002677121,0.0005035609,0.0002842174],"domain_scores_gemma":[0.9980727,0.0001023767,0.0004084056,0.0003420795,0.0009585566,0.0001158747],"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":[0.0001294972,0.0001531013,0.0009844871,0.0003615106,0.000188667,0.0000354882,0.0002081795,0.0007704366,0.9959164,0.00005622206,0.00003440533,0.001161614],"study_design_scores_gemma":[0.0002950381,0.00009033927,0.001101714,0.0001074695,0.000123165,0.00001094065,0.0001898077,0.003067912,0.9892395,0.005638593,0.00003192157,0.0001035999],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883614,0.004791857,0.005805431,0.0004845022,0.00001158491,0.0003265984,0.0001148401,0.00001182199,0.00009202748],"genre_scores_gemma":[0.9806608,0.002443438,0.01586737,0.000009558592,0.0001554774,0.0001908751,0.00002296078,0.00001889515,0.0006306395],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01006193,"threshold_uncertainty_score":0.477169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04058788297702329,"score_gpt":0.3537481405908043,"score_spread":0.313160257613781,"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."}}