{"id":"W4407793404","doi":"10.1021/acs.analchem.4c05859","title":"From Reverse Phase Chromatography to HILIC: Graph Transformers Power Method-Independent Machine Learning of Retention Times","year":2025,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Foundation for Innovation; Ontario Research Foundation","keywords":"Chemistry; Hydrophilic interaction chromatography; Chromatography; Reversed-phase chromatography; High-performance liquid chromatography","routes":{"ca_aff":true,"ca_fund":true,"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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002971883,0.0005000659,0.0008054877,0.0001571595,0.0001507183,0.00005213532,0.0005293336,0.0005063735,0.01084327],"category_scores_gemma":[0.0002395866,0.000498739,0.001023582,0.00121428,0.0002586263,0.0001110581,0.0001236889,0.0007957449,0.00002248821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006262359,"about_ca_system_score_gemma":0.00008753408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001682614,"about_ca_topic_score_gemma":0.000002909508,"domain_scores_codex":[0.9969083,0.00003695019,0.0009278643,0.0009171104,0.00061942,0.0005903371],"domain_scores_gemma":[0.9982557,0.0002773765,0.0001899481,0.0006271329,0.000174929,0.0004748896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004916663,0.0008241059,0.004939382,0.0008479458,0.001350744,0.00004117032,0.0001301647,0.0000565167,0.9873595,0.0005300667,0.002372476,0.00105627],"study_design_scores_gemma":[0.002255657,0.00005028323,0.0001085121,0.0004226022,0.0009145653,0.00001010974,0.0008878594,0.005425675,0.9727075,0.002070404,0.01451854,0.0006283592],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.701433,0.0004657202,0.03950473,0.0009330685,0.00006635286,0.000161,0.0004944605,0.0003474293,0.2565942],"genre_scores_gemma":[0.9926441,0.00005205427,0.001139527,0.0001517751,0.00007890609,0.00002138394,0.0005611777,0.00003843111,0.005312645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2912111,"threshold_uncertainty_score":0.9997464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00875667506143666,"score_gpt":0.2849015465703224,"score_spread":0.2761448715088857,"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."}}