{"id":"W2521910883","doi":"10.1007/8623_2016_5","title":"Sample Preparation of Rhodopsins in the E. coli Membrane for In Situ Magic Angle Spinning Solid-State Nuclear Magnetic Resonance Studies","year":2016,"lang":"en","type":"book-chapter","venue":"Springer protocols handbooks/Springer protocols","topic":"Photoreceptor and optogenetics research","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Solid-state nuclear magnetic resonance; Membrane; Magic angle spinning; Transmembrane protein; Membrane protein; Biophysics; Nuclear magnetic resonance spectroscopy; Rhodopsin; Native state; Transmembrane domain; Chemistry; Biochemistry; Crystallography; Biology; Nuclear magnetic resonance; Stereochemistry; Physics; Receptor","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005355516,0.0006025002,0.0005484784,0.0005189506,0.0006947821,0.0005163343,0.0007838603,0.0005468581,0.007446765],"category_scores_gemma":[0.0006007505,0.0005494176,0.0002973883,0.0007029632,0.0003233317,0.0004974081,0.0003359338,0.001537413,0.005931274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003741859,"about_ca_system_score_gemma":0.0005829555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001073889,"about_ca_topic_score_gemma":0.002721605,"domain_scores_codex":[0.9997599,0.00002810517,0.0000182872,0.00005637341,0.0001003836,0.0000370764],"domain_scores_gemma":[0.9997684,0.00006426433,0.00002229989,0.00005338101,0.00006971983,0.00002185733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004392358,0.00002609767,0.00005625905,0.0001497124,0.000007179674,0.00004888379,0.00003623759,0.000112447,0.9930708,0.000611201,0.0008082775,0.005028909],"study_design_scores_gemma":[0.0000173792,0.00008273655,0.0005232571,0.0000332358,0.00001234371,0.000133494,0.00004203538,0.0006942003,0.9750489,0.0005555197,0.02284353,0.00001336955],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3111771,0.01290018,0.6152759,0.00178981,0.001247658,0.002328178,0.01611405,0.003963493,0.03520371],"genre_scores_gemma":[0.3321002,0.02593333,0.5548269,0.00112035,0.0002387555,0.003375079,0.03347313,0.00228675,0.04664563],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007446765,"threshold_uncertainty_score":0.02491194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1313083549241956,"score_gpt":0.4066688026031957,"score_spread":0.2753604476790001,"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."}}