{"id":"W2526539642","doi":"10.1016/j.micron.2016.09.010","title":"Practical electron tomography guide: Recent progress and future opportunities","year":2016,"lang":"en","type":"article","venue":"Micron","topic":"Advanced Electron Microscopy Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Institute for Nanotechnology","funders":"Alberta Innovates - Technology Futures; National Institute for Nanotechnology","keywords":"Electron tomography; Tomography; Tomographic reconstruction; Volume (thermodynamics); Focus (optics); Medical physics; Computed tomography; Materials science; Engineering physics; Computer science; Nanotechnology; Physics; Optics; Medicine; Radiology","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":[0.002926445,0.001402563,0.000765121,0.002221159,0.0004311835,0.001771069,0.002521273,0.002998848,0.04429616],"category_scores_gemma":[0.003844939,0.0009142543,0.0005464257,0.001512484,0.001074203,0.003091925,0.001265412,0.002950437,0.02906075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000655497,"about_ca_system_score_gemma":0.002101173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001713336,"about_ca_topic_score_gemma":0.00658114,"domain_scores_codex":[0.9994815,0.0001199156,0.00004393813,0.00004177877,0.0002854702,0.00002735],"domain_scores_gemma":[0.9967684,0.001441398,0.0001239266,0.0002961878,0.001159431,0.0002107001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001405506,0.00009998302,0.0004573095,0.001595914,0.00001874908,0.0003353707,0.0001264987,0.002055213,0.007925508,0.01437631,0.4760018,0.4968669],"study_design_scores_gemma":[0.00002769757,0.00008154925,0.0004350084,0.0003796138,0.00001327225,0.003127447,0.00009771866,0.003976416,0.003299507,0.01073095,0.9777834,0.00004749482],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001775118,0.1719263,0.7286269,0.01781599,0.006246687,0.0004171121,0.002987308,0.01740505,0.05279947],"genre_scores_gemma":[0.006545949,0.1290203,0.7405394,0.00682206,0.001916989,0.0006628621,0.002966665,0.002923939,0.1086018],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04429616,"threshold_uncertainty_score":0.1481854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01551236829094671,"score_gpt":0.3444987059197297,"score_spread":0.328986337628783,"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."}}