{"id":"W2015562215","doi":"10.1517/17530059.2012.634797","title":"Bioinformatics advances for clinical biomarker development","year":2011,"lang":"en","type":"article","venue":"Expert Opinion on Medical Diagnostics","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bayer (Canada); University of Toronto; Mount Sinai Hospital","funders":"","keywords":"Biomarker; Biomarker discovery; Standardization; Bioinformatics; Clinical Practice; Medicine; Computer science; Data science; Computational biology; Biology; Proteomics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006102989,0.0003684836,0.0009066279,0.0001049945,0.0001714005,0.00002632388,0.0006914517,0.0006185,0.001538533],"category_scores_gemma":[0.4567251,0.0002781321,0.0002781274,0.0001896823,0.0005026528,0.00009875168,0.0001967288,0.0004660275,0.0002348318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005592473,"about_ca_system_score_gemma":0.0002942907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000151221,"about_ca_topic_score_gemma":0.00000151995,"domain_scores_codex":[0.9944658,0.0005377477,0.002664124,0.0005118472,0.001222191,0.0005982863],"domain_scores_gemma":[0.865793,0.132067,0.0004725161,0.0006010314,0.0002337287,0.0008327884],"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":[0.0003266728,0.001564214,0.000665083,0.0001429285,0.0001161319,0.00001451298,0.0006280885,4.641747e-8,3.522907e-7,0.1042359,0.1627358,0.7295702],"study_design_scores_gemma":[0.003028184,0.000942115,0.00185375,0.00077882,0.00001705233,0.000006535412,0.0002032853,0.0009688325,0.0004258232,0.3057136,0.6854519,0.0006100812],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003390928,0.001570208,0.9762645,0.001141159,0.01194045,0.001465792,0.00008035212,0.0003203197,0.006878133],"genre_scores_gemma":[0.0003340282,0.0185737,0.9755287,0.003961046,0.001117309,0.0003523816,0.00001886263,0.00006567343,0.00004830363],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7289602,"threshold_uncertainty_score":0.9999671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7448562009410405,"score_gpt":0.6231279349601743,"score_spread":0.1217282659808663,"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."}}