{"id":"W2089467148","doi":"10.1021/ja076658v","title":"Dipolar Chemical Shift Correlation Spectroscopy for Homonuclear Carbon Distance Measurements in Proteins in the Solid State:  Application to Structure Determination and Refinement","year":2007,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Advanced NMR Techniques and Applications","field":"Chemistry","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Homonuclear molecule; Chemistry; Chemical shift; Solid-state nuclear magnetic resonance; Spectroscopy; Intramolecular force; Nuclear magnetic resonance spectroscopy; Two-dimensional nuclear magnetic resonance spectroscopy; Crystallography; Analytical Chemistry (journal); Chemical physics; Molecule; Nuclear magnetic resonance; Physical chemistry; Stereochemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.0003310333,0.000115734,0.0001842939,0.00001680955,0.00005253192,0.00001786701,0.0002878984,0.00005364165,0.000001399924],"category_scores_gemma":[0.00007261433,0.000078777,0.00008955165,0.000281712,0.0001052709,0.00004701526,0.00004424662,0.000364177,5.711249e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004124498,"about_ca_system_score_gemma":0.00002112217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000304286,"about_ca_topic_score_gemma":0.00002127375,"domain_scores_codex":[0.998925,0.0000117594,0.000401374,0.0001656055,0.0002972924,0.0001990108],"domain_scores_gemma":[0.9991612,0.00007777361,0.0004530611,0.0001983751,0.00006133717,0.00004822827],"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":[0.00007868956,0.00007213608,0.005608269,0.00002046114,0.00000635945,1.419896e-7,0.0006959218,0.0000741039,0.9881626,0.00001829328,0.00004087629,0.005222118],"study_design_scores_gemma":[0.0004466968,0.00004309482,0.006815442,0.00006808529,0.00002063993,0.0000063544,0.0003339578,0.001957235,0.9867545,0.002454984,0.0009696222,0.0001293497],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9575585,0.00003011947,0.04089154,0.001094087,0.000005975722,0.0003661316,0.00001198974,0.000008663227,0.00003303736],"genre_scores_gemma":[0.9756677,0.00001695652,0.0239254,0.0002399064,0.00008172287,0.00004665844,0.000004312799,0.00001393696,0.000003477486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01810917,"threshold_uncertainty_score":0.3212433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008592544733452081,"score_gpt":0.2937390317174664,"score_spread":0.2851464869840143,"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."}}