{"id":"W2008546870","doi":"10.1016/j.ymeth.2006.07.019","title":"Structural analysis of membrane protein complexes by single particle electron microscopy","year":2007,"lang":"en","type":"article","venue":"Methods","topic":"Advanced Electron Microscopy Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Single particle analysis; Resolution (logic); Crystallography; Particle (ecology); Electron microscope; Membrane protein; Cryo-electron microscopy; Membrane; Chemistry; Macromolecule; Structural biology; Electron crystallography; Electron micrographs; Protein structure; Chemical physics; Biology; Physics; Biochemistry; Electron diffraction; Diffraction; Computer science; Optics; Organic chemistry","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":[0.0003786876,0.0001101807,0.0001942766,0.00004447865,0.00006036819,0.000008534458,0.0001441941,0.00007818452,0.00002330025],"category_scores_gemma":[0.00003111318,0.0001057347,0.0001024798,0.0004202733,0.00008643696,0.000002988205,0.00003802171,0.00006455036,3.93915e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001829542,"about_ca_system_score_gemma":0.00001280827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002861618,"about_ca_topic_score_gemma":0.00003173241,"domain_scores_codex":[0.9991093,0.00006730654,0.0002383756,0.0002485767,0.00006055943,0.0002758397],"domain_scores_gemma":[0.9994693,0.00002054941,0.0001119332,0.000293226,0.0000559842,0.0000489692],"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":[0.00005001379,0.00003789325,0.0002872579,0.000005141327,0.0001060864,7.49008e-8,0.00001113498,0.00002305079,0.9956459,0.0002755204,0.00009992483,0.003458048],"study_design_scores_gemma":[0.0001062584,0.0002011829,0.0002973564,0.000001758508,0.00008984155,9.914095e-7,0.00001004601,0.0001015739,0.9884666,0.0002004062,0.01040894,0.0001150911],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5957459,0.0004474904,0.4035515,0.00002449106,0.000004872285,0.0001213142,0.00001612364,0.00001351412,0.0000747575],"genre_scores_gemma":[0.6598991,0.0000123724,0.3395978,0.00005363248,0.00001617949,0.00001460406,0.0001143139,0.00001156173,0.0002804548],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06415318,"threshold_uncertainty_score":0.4311737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01489793382375367,"score_gpt":0.417702695901007,"score_spread":0.4028047620772534,"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."}}