{"id":"W2762010667","doi":"10.3390/proteomes5040025","title":"Differential Proteome Analysis of Extracellular Vesicles from Breast Cancer Cell Lines by Chaperone Affinity Enrichment","year":2017,"lang":"en","type":"article","venue":"Proteomes","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; Atlantic Cancer Research Institute","funders":"Dalhousie University; Breast Cancer Society of Canada; Beatrice Hunter Cancer Research Institute; Cancer Research Institute","keywords":"Proteome; SKBR3; Chaperone (clinical); Biology; Cancer cell; Heat shock protein; Computational biology; Proteomics; Biomarker discovery; Phenotype; Cell biology; Cell; Cell culture; Cancer; Biochemistry; Gene; Human breast; 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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001188591,0.0002873887,0.0004074258,0.00005345341,0.0002336085,0.00008921418,0.0007261198,0.0001837341,0.001042836],"category_scores_gemma":[0.00004952536,0.0002647837,0.000285334,0.00007631971,0.0002355007,0.00001884092,0.0003574434,0.0001015563,0.000008941581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002763621,"about_ca_system_score_gemma":0.00006766507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009059254,"about_ca_topic_score_gemma":0.0001128048,"domain_scores_codex":[0.9983029,0.00007967521,0.0003853174,0.0006061452,0.0003026249,0.000323387],"domain_scores_gemma":[0.9979936,0.00001180089,0.0005083907,0.001193947,0.0001242973,0.0001678922],"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":[0.0001443097,0.0004503817,0.03439821,0.00004936556,0.0007387286,0.00000355745,0.00005688311,0.00002925365,0.9617302,0.000006656482,0.0002419557,0.002150504],"study_design_scores_gemma":[0.0006462226,0.00006799369,0.08812729,0.00001914717,0.0006698021,3.888536e-7,0.00003369493,0.0003128854,0.909128,0.00004464297,0.0006488105,0.0003010848],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894096,0.00658711,0.001213454,0.0001925801,0.0001062683,0.0006157508,0.00173992,0.00001859903,0.0001167259],"genre_scores_gemma":[0.9969327,0.000606619,0.0006792553,0.00002067237,0.0002742256,0.0002562912,0.0004618934,0.00003618503,0.0007321602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05372908,"threshold_uncertainty_score":0.9999804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009538096342241342,"score_gpt":0.2577567355055072,"score_spread":0.2482186391632659,"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."}}