{"id":"W4412163815","doi":"10.1158/1557-3265.aimachine-a019","title":"Abstract A019: A fully transparent and automatable form of AI for biomarker and new target discovery using diverse multi-omics data","year":2025,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biomarker; Biomarker discovery; Computational biology; Omics; Computer science; Bioinformatics; Medicine; Biology; Proteomics; Genetics; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002986236,0.0006776445,0.0005064529,0.001722741,0.001268742,0.002927953,0.001802758,0.001091949,0.006280568],"category_scores_gemma":[0.009153801,0.0004808765,0.001564668,0.0009582936,0.002832771,0.003742598,0.004377201,0.002154968,0.00158179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001071283,"about_ca_system_score_gemma":0.002190575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003977456,"about_ca_topic_score_gemma":0.003989856,"domain_scores_codex":[0.9975278,0.0009266973,0.0001730936,0.0006760522,0.0005798775,0.0001165009],"domain_scores_gemma":[0.9933083,0.002447507,0.0005156565,0.002442133,0.0008938136,0.0003925793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002324308,0.0001445213,0.002345496,0.0002915781,0.0001624486,0.0005172127,0.0005917969,0.1241113,0.02195958,0.7376108,0.01423466,0.09779804],"study_design_scores_gemma":[0.00003133161,0.00007218745,0.0003007948,0.00004804587,0.00005834239,0.0001094177,0.0001056533,0.5099023,0.008845313,0.4567882,0.02368878,0.00004966664],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007551488,0.00009723387,0.9838803,0.000892016,0.0001204319,0.00009659623,0.0003768233,0.002755556,0.004229478],"genre_scores_gemma":[0.3235556,0.0002268,0.6671273,0.0006823295,0.0001353994,0.0003056269,0.001014828,0.0006025558,0.006349553],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006280568,"threshold_uncertainty_score":0.02101058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3695402611117912,"score_gpt":0.5258084279340924,"score_spread":0.1562681668223013,"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."}}