{"id":"W2005497218","doi":"10.1016/j.jprot.2010.04.003","title":"The cancer cell secretome: A good source for discovering biomarkers?","year":2010,"lang":"en","type":"review","venue":"Journal of Proteomics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":202,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network; University of Toronto; Mount Sinai Hospital","funders":"","keywords":"Biomarker discovery; Proteomics; Biomarker; Cancer; Cancer biomarkers; Prostate cancer; Pancreatic cancer; Medicine; Colorectal cancer; Breast cancer; Computational biology; Bioinformatics; Biology; Internal medicine","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":[0.001786826,0.001720143,0.003819278,0.002690442,0.0004046716,0.00237765,0.001846959,0.002732563,0.002180256],"category_scores_gemma":[0.001912064,0.0006955078,0.0006371734,0.002730035,0.001339589,0.004221914,0.001169962,0.003386082,0.003880344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008961568,"about_ca_system_score_gemma":0.001079837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006341983,"about_ca_topic_score_gemma":0.0009585703,"domain_scores_codex":[0.9995033,0.00006814479,0.00004091747,0.00008061167,0.0002631168,0.000043974],"domain_scores_gemma":[0.9983789,0.0007758511,0.0001786002,0.00007789416,0.000458064,0.0001306669],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001404446,0.00008368705,0.0003259713,0.007205495,0.0001192089,0.0003207622,0.00003863185,0.0002429244,0.01076656,0.00647571,0.06009701,0.9141836],"study_design_scores_gemma":[0.00003593538,0.0001158695,0.0006060953,0.001488858,0.0001302608,0.001926862,0.00008040255,0.0002423768,0.004950732,0.007252188,0.983124,0.00004634621],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001760862,0.9959164,0.001195378,0.001259196,0.000572702,0.000007868161,0.00005869348,0.00002702995,0.0007865921],"genre_scores_gemma":[0.001092452,0.9948601,0.001549969,0.0008046558,0.0006112806,0.00001505661,0.0001002298,0.000005816466,0.0009604517],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003819278,"threshold_uncertainty_score":0.00944978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02322681819782219,"score_gpt":0.3413653621722245,"score_spread":0.3181385439744023,"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."}}