{"id":"W4417424063","doi":"10.1038/s42004-025-01839-x","title":"Structure characterization with NMR molecular networking","year":2025,"lang":"en","type":"article","venue":"Communications Chemistry","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Heteronuclear single quantum coherence spectroscopy; Workflow; Heteronuclear molecule; Annotation; Coherence (philosophical gambling strategy); Key (lock); Characterization (materials science); Metric (unit)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001050338,0.0001067256,0.00009937521,0.00003879498,0.0001890999,0.0001517426,0.001947591,0.00005320977,0.000007446543],"category_scores_gemma":[0.00003035823,0.000106973,0.00002939846,0.0007109348,0.00007851824,0.0002141703,0.0007656337,0.0001943335,0.000001863576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005916212,"about_ca_system_score_gemma":0.0001630221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001747158,"about_ca_topic_score_gemma":9.678193e-7,"domain_scores_codex":[0.999278,0.00008232008,0.0001613652,0.0002244317,0.0001270972,0.0001268015],"domain_scores_gemma":[0.997578,0.0001470295,0.00008629626,0.002028653,0.0001264833,0.00003359502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001671339,0.000197516,0.003194118,0.0001549894,0.0001876672,0.000007856921,0.0005232669,0.02249123,0.591692,0.1831982,0.0002777245,0.1980587],"study_design_scores_gemma":[0.000611262,0.00001179148,0.01274336,0.0003074944,0.00004316353,0.00003706276,0.00003746792,0.7528219,0.1608482,0.03049334,0.04147466,0.0005703489],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07028684,0.0003148294,0.9177548,0.002653913,0.00005732113,0.00009815652,0.000005741018,0.000143503,0.008684854],"genre_scores_gemma":[0.886921,0.00002796653,0.1122274,0.0003892921,0.00002176693,0.00002187372,0.0001589492,0.000007010011,0.000224698],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8166342,"threshold_uncertainty_score":0.4362233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009702602144901767,"score_gpt":0.2775054292870581,"score_spread":0.2678028271421564,"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."}}