{"id":"W2560164881","doi":"10.1017/s143192761500104x","title":"Imaging Macromolecules and Viruses in a Hydrated State Using a Field Emission Scanning Electron Microscope (FESEM)","year":2015,"lang":"en","type":"article","venue":"Microscopy and Microanalysis","topic":"Advanced Electron Microscopy Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Field emission microscopy; State (computer science); Field (mathematics); Nanotechnology; Art history; Library science; Materials science; Analytical Chemistry (journal); Chemistry; Art; Physics; Optics; Computer science; Mathematics; Chromatography","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000219236,0.0002653316,0.0002719644,0.0001682097,0.0001615341,0.0001003558,0.0001381048,0.0001072517,0.000002974221],"category_scores_gemma":[0.0000370532,0.0002710434,0.00005726511,0.0003275805,0.0001135527,0.00002010437,0.0001728467,0.0001752005,9.774799e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000545582,"about_ca_system_score_gemma":0.0001013777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004664467,"about_ca_topic_score_gemma":0.0001284587,"domain_scores_codex":[0.9984981,0.00006302552,0.000317936,0.0005989855,0.00007192073,0.000449986],"domain_scores_gemma":[0.9993656,0.00001147759,0.0001247253,0.000266641,0.00007980812,0.0001517581],"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":[0.0001182994,0.00003810967,0.01361479,0.00001317045,0.00003195047,0.000005110227,0.0001140867,0.00003499509,0.9843847,0.000003775604,0.0003824147,0.001258666],"study_design_scores_gemma":[0.0005095235,0.0001075251,0.000122812,0.00004974489,0.00005372638,0.00005217799,0.0001494071,0.0004669989,0.9932372,0.0001836932,0.00476304,0.0003041829],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9632196,0.009616583,0.02674766,0.0001189082,0.00001412759,0.0001933112,0.00001866455,0.00002542498,0.00004569757],"genre_scores_gemma":[0.982107,0.001018058,0.01582485,0.0006984822,0.00002997252,0.0000228069,0.00006098022,0.00004069739,0.0001971897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01888735,"threshold_uncertainty_score":0.9999742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01103912901752403,"score_gpt":0.33266326746227,"score_spread":0.321624138444746,"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."}}