{"id":"W4410014280","doi":"10.1016/j.microb.2025.100368","title":"Integrative research: Current trends and considerations for biomarker discovery and precision medicine","year":2025,"lang":"en","type":"article","venue":"The Microbe","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Precision medicine; Biomarker discovery; Data science; Current (fluid); Biomarker; Medicine; Medical physics; Computer science; Biology; Engineering; Pathology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0594683,0.002066707,0.003296044,0.004855191,0.002603609,0.01540981,0.004996791,0.012409,0.0117506],"category_scores_gemma":[0.03624035,0.000986888,0.002170942,0.005551007,0.02528453,0.02881341,0.008044557,0.01814556,0.004538835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009315411,"about_ca_system_score_gemma":0.01610392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00281328,"about_ca_topic_score_gemma":0.002529486,"domain_scores_codex":[0.9763075,0.0144001,0.001415907,0.002009357,0.004967519,0.0008995593],"domain_scores_gemma":[0.9098012,0.07028507,0.002051192,0.004707621,0.009108186,0.004046702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000163074,0.0001255955,0.0008717801,0.005545093,0.0001447662,0.0002546036,0.00108834,0.000821194,0.0005897077,0.6002407,0.09054022,0.299615],"study_design_scores_gemma":[0.00004184892,0.0001113528,0.0005681629,0.005259083,0.00006307788,0.0006561877,0.0009330506,0.0008952986,0.0002134915,0.4849373,0.5062436,0.00007751797],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.0003780805,0.7482717,0.0239201,0.2127202,0.005082143,0.00006352406,0.00009293952,0.000176452,0.009294841],"genre_scores_gemma":[0.01487079,0.8545183,0.04441286,0.0621369,0.02049477,0.000371519,0.0002476356,0.0001835324,0.002763745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0594683,"threshold_uncertainty_score":0.3145022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05648689499976171,"score_gpt":0.3801002445347357,"score_spread":0.3236133495349739,"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."}}