{"id":"W2090166572","doi":"10.1002/prca.200800019","title":"A qualitative proteome investigation of the sediment portion of human urine: Implications in the biomarker discovery process","year":2008,"lang":"en","type":"article","venue":"PROTEOMICS - CLINICAL APPLICATIONS","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Izaak Walton Killam Health Centre; Institute for Marine Biosciences; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Dalhousie University","keywords":"Biomarker discovery; Proteome; Biomarker; Urine; Computational biology; Process (computing); Sediment; Human proteome project; Biology; Proteomics; Bioinformatics; Medicine; Computer science; Internal medicine; Genetics; Gene; Paleontology","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":[0.001011744,0.0002016723,0.0003371043,0.00006919097,0.0003457298,0.0000147674,0.0009249484,0.0001898241,0.00001575656],"category_scores_gemma":[0.0001836807,0.0001407469,0.0002224336,0.0008580073,0.0009766814,0.000184185,0.0001369851,0.0004855967,0.000002496587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006850495,"about_ca_system_score_gemma":0.0002174974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006703311,"about_ca_topic_score_gemma":0.00001702841,"domain_scores_codex":[0.9972503,0.0001469909,0.001611518,0.0004639429,0.0003124386,0.0002148323],"domain_scores_gemma":[0.9967704,0.0003950294,0.001298006,0.001195172,0.0002810938,0.00006023116],"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":[0.00007996866,0.001894983,0.1002731,0.0004640018,0.0000879122,3.044447e-7,0.005211173,0.0001025347,0.7426412,0.1481414,0.0002007321,0.0009026703],"study_design_scores_gemma":[0.000983439,0.00009231801,0.08975538,0.0001525473,0.00008529096,0.00001660654,0.001300489,0.0002063751,0.5357289,0.3707334,0.00053398,0.0004112197],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9452196,0.0000264958,0.04643319,0.003192961,0.000008785421,0.003938949,0.0001960585,0.00005449606,0.0009294309],"genre_scores_gemma":[0.9698433,0.00006303792,0.01538151,0.0001341662,0.00005959901,0.01425088,0.0001207579,0.0000263889,0.0001204217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.222592,"threshold_uncertainty_score":0.5739493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1060451235873162,"score_gpt":0.4403117094601121,"score_spread":0.3342665858727958,"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."}}