{"id":"W4406545476","doi":"10.3389/fmolb.2024.1545016","title":"Editorial: Metabolomics and transcriptomics in biomarker discovery: mass spectrometric techniques in volatilome research","year":2025,"lang":"en","type":"editorial","venue":"Frontiers in Molecular Biosciences","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome British Columbia; University of British Columbia","funders":"","keywords":"Biology; Computational biology; Transcriptome; Metabolomics; Population; Genome; Genetics; Bioinformatics; Gene; Gene expression","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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.004185449,0.0005627428,0.001053944,0.004508548,0.0001142253,0.0002776358,0.001129722,0.001391032,0.00000141838],"category_scores_gemma":[0.002686031,0.0005503749,0.0001637334,0.004454869,0.0007884263,0.00003786109,0.000471691,0.001316912,3.169275e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002719391,"about_ca_system_score_gemma":0.0007970095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004018152,"about_ca_topic_score_gemma":0.0004755424,"domain_scores_codex":[0.9947468,0.0005602744,0.0008133578,0.001674779,0.001139758,0.001065045],"domain_scores_gemma":[0.9987299,0.0001467277,0.0001895925,0.0006295788,0.000203525,0.0001006765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000225578,0.0001413199,0.004611189,0.0001263467,0.00008005546,0.00002752794,0.00005622945,0.00000334264,0.214608,0.0001867165,0.7787824,0.001151384],"study_design_scores_gemma":[0.001115332,0.0003633045,0.0006602466,0.000177622,0.00003998091,7.517619e-7,0.0004323048,0.00008717611,0.03787871,0.004221763,0.9542115,0.0008112717],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.01884464,0.03243035,0.005419804,0.0002642032,0.9406751,0.001103665,0.0002774024,0.00001962783,0.0009651888],"genre_scores_gemma":[0.04004638,0.1732998,0.06878413,0.0001543095,0.7137913,0.000739228,0.0007839262,0.0002217002,0.002179272],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.2268839,"threshold_uncertainty_score":0.9999053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009765058129746639,"score_gpt":0.2977342706395337,"score_spread":0.287969212509787,"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."}}