{"id":"W31737416","doi":"10.1385/cp:2:1:5","title":"Proteomic and genomic technologies for biomarker discovery","year":2006,"lang":"en","type":"article","venue":"Clinical Proteomics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Mount Sinai Hospital","funders":"","keywords":"Biomarker discovery; Proteomics; Biomarker; Computational biology; Bioinformatics; Data science; Medicine; Biology; Computer science; Genetics","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":[0.001974609,0.000678164,0.0009785034,0.001734237,0.0004127741,0.001603417,0.0007788764,0.001277755,0.00377619],"category_scores_gemma":[0.002494654,0.0003157989,0.0006090498,0.001521619,0.000989459,0.001722907,0.0009210878,0.001633086,0.002530589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006913336,"about_ca_system_score_gemma":0.0008937449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003724108,"about_ca_topic_score_gemma":0.0003897788,"domain_scores_codex":[0.9992546,0.0003379219,0.00004131417,0.00009999561,0.0002189116,0.00004713801],"domain_scores_gemma":[0.9992298,0.0003540962,0.00007590582,0.0001206674,0.0001516942,0.00006797304],"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":[0.0006369946,0.0002975413,0.00513096,0.002280881,0.0002704802,0.001203082,0.0001520363,0.002509211,0.188656,0.1494966,0.02349891,0.6258673],"study_design_scores_gemma":[0.0001642547,0.0006007995,0.008976083,0.000456099,0.000390475,0.007132613,0.0003261011,0.01029389,0.1218729,0.4231762,0.4264832,0.0001273431],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.03760559,0.3473528,0.5300599,0.03736844,0.005562045,0.0003442325,0.003259476,0.001938903,0.03650869],"genre_scores_gemma":[0.3202325,0.2083789,0.4263937,0.01590658,0.008168583,0.0006328626,0.003430894,0.0001565098,0.01669949],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.00377619,"threshold_uncertainty_score":0.01263261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03393678040176136,"score_gpt":0.3421906406370843,"score_spread":0.308253860235323,"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."}}