{"id":"W2095273987","doi":"10.1021/pr0700798","title":"Identification of Candidate Biomarker Proteins Released by Human Endometrial and Cervical Cancer Cells Using Two-Dimensional Liquid Chromatography/Tandem Mass Spectrometry","year":2007,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Toronto; St. Michael's Hospital; Mount Sinai Hospital","funders":"Scheme for Promotion of Academic and Research Collaboration","keywords":"HeLa; Proteome; Chemistry; Biomarker; Mass spectrometry; Tandem mass spectrometry; Proteomics; Chromatography; Biomarker discovery; Cervical cancer; Endometrial cancer; Liquid chromatography–mass spectrometry; Cancer; Molecular biology; Biochemistry; Biology; Cell; Gene","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":[0.0002077672,0.0004382578,0.0003926147,0.0007661369,0.0002716861,0.0004463232,0.0001924402,0.0004626585,0.0004762126],"category_scores_gemma":[0.0004351972,0.0001477907,0.0002641059,0.0005153276,0.0001691536,0.000159679,0.0001856887,0.0003216281,0.0003926086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002168432,"about_ca_system_score_gemma":0.000259114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006194941,"about_ca_topic_score_gemma":0.001001101,"domain_scores_codex":[0.9998578,0.00002055863,0.00001562688,0.00003005563,0.00005662162,0.00001939644],"domain_scores_gemma":[0.999862,0.00003528734,0.00003197607,0.000009572295,0.00003758554,0.00002371752],"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":[0.0002193019,0.00003201106,0.00259813,0.0000885097,0.00002271163,0.000186823,0.00004202705,0.00005190356,0.9932926,0.00005245046,0.0001170295,0.003296522],"study_design_scores_gemma":[0.00007935218,0.0005966385,0.06920237,0.00002943584,0.000123141,0.003103073,0.0001320213,0.002871229,0.9184917,0.0001393641,0.005186017,0.00004555361],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9775715,0.007414511,0.0112865,0.0002636891,0.00006347435,0.0001402755,0.002263871,0.0001440409,0.0008519624],"genre_scores_gemma":[0.9348987,0.007291814,0.04570669,0.0004504338,0.00007459656,0.0003903927,0.007190697,0.00004189291,0.003954779],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007661369,"threshold_uncertainty_score":0.001593113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03364023089808249,"score_gpt":0.3770531699578509,"score_spread":0.3434129390597684,"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."}}