{"id":"W3131596152","doi":"10.1016/j.cell.2021.01.033","title":"DNA origami signposts for identifying proteins on cell membranes by electron cryotomography","year":2021,"lang":"en","type":"article","venue":"Cell","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Engineering and Physical Sciences Research Council; Medical Research Council; Canadian Institutes of Health Research; Wellcome Trust","keywords":"Biology; DNA origami; Cryo-electron tomography; DNA; Biophysics; Cell biology; Lipid bilayer fusion; Electron tomography; Membrane; Cryo-electron microscopy; Computational biology; Membrane protein; Nanotechnology; Biochemistry; Tomography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002011447,0.0002893351,0.0001707446,0.0002307189,0.0002264078,0.0003813281,0.0003509401,0.0004478688,0.0009514137],"category_scores_gemma":[0.000335052,0.000202494,0.0001730613,0.0001471656,0.0003054735,0.000356425,0.0003679789,0.0007159165,0.0004487205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002990886,"about_ca_system_score_gemma":0.000165285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003349865,"about_ca_topic_score_gemma":0.0008111255,"domain_scores_codex":[0.9999014,0.00001084016,0.000006662046,0.00002064523,0.00004653304,0.00001390598],"domain_scores_gemma":[0.9998562,0.00004262823,0.00002865269,0.00002417926,0.00002970285,0.00001871036],"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":[0.000006548117,0.00000263184,0.00002973426,0.00001077012,7.85898e-7,0.00001781109,0.00000878029,0.00003331925,0.9989883,0.0001549146,0.00002164765,0.0007247427],"study_design_scores_gemma":[0.000001756247,0.00002200021,0.0002940173,0.000002816182,0.000002336521,0.00008682435,0.00001152917,0.001309829,0.9969882,0.00006315937,0.001214322,0.000003091211],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8285817,0.002030763,0.1633479,0.0004018838,0.0001485862,0.0001779165,0.0005112716,0.0004649971,0.004335166],"genre_scores_gemma":[0.8266336,0.00218433,0.1635776,0.0002397913,0.00002944267,0.0001974843,0.0005199344,0.0000710583,0.00654671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009514137,"threshold_uncertainty_score":0.003182769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008785501320865006,"score_gpt":0.2630487850067922,"score_spread":0.2542632836859272,"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."}}