{"id":"W4414227488","doi":"10.26434/chemrxiv-2025-0nqfk","title":"Structure Characterization with NMR Molecular Networking","year":2025,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Molecular spectroscopy and chirality","field":"Chemistry","cited_by":0,"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; Key (lock); Characterization (materials science); Coherence (philosophical gambling strategy); 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00004608657,0.0004156925,0.0003870129,0.00004283171,0.00008135902,0.0001218785,0.0004431256,0.0005602558,0.0005757574],"category_scores_gemma":[0.00001035867,0.0003948486,0.0001410219,0.0001265176,0.00005575159,0.00003157862,0.000382232,0.0009669433,0.000002853154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001017319,"about_ca_system_score_gemma":0.000167326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001185131,"about_ca_topic_score_gemma":0.000005094131,"domain_scores_codex":[0.99843,0.00002050146,0.0002692617,0.0006991417,0.000256591,0.0003244833],"domain_scores_gemma":[0.9986258,0.000009504104,0.0002565011,0.0009527421,0.00007375112,0.0000817512],"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":[0.00006692835,0.00004348717,0.003115033,0.001393936,0.0002696652,0.00007114952,0.0001440989,0.0004501314,0.9922395,0.0007070622,0.00006368581,0.001435271],"study_design_scores_gemma":[0.0002797662,0.000006537479,0.0003974425,0.0007416652,0.0001582812,0.000005737797,0.000005901812,0.0006912324,0.9890236,0.001199964,0.006980938,0.000508884],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9629581,0.0003596044,0.009052688,0.0001886626,0.0002920666,0.0001536289,0.00005629473,0.0002266371,0.02671233],"genre_scores_gemma":[0.9947056,0.00005988446,0.0007087176,0.0003163779,0.0005246725,0.00003966778,0.001942686,0.00004478676,0.001657601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03174752,"threshold_uncertainty_score":0.9998503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006352932991064298,"score_gpt":0.23188356052132,"score_spread":0.2255306275302557,"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."}}