{"id":"W2513086024","doi":"10.1016/bs.mie.2016.04.009","title":"Processing of Cryo-EM Movie Data","year":2016,"lang":"en","type":"review","venue":"Methods in enzymology on CD-ROM/Methods in enzymology","topic":"Advanced Electron Microscopy Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Canadian Institutes of Health Research; Hospital for Sick Children; Canada Research Chairs","keywords":"Detective quantum efficiency; Detector; Cryo-electron microscopy; Computer vision; Computer science; Reference frame; Frame (networking); Notation; Contrast (vision); Artificial intelligence; Optics; Computer graphics (images); Image (mathematics); Image quality; Physics; Telecommunications; Mathematics","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":[0.0008953388,0.001422727,0.001169638,0.002717648,0.0003678908,0.001034972,0.001949154,0.0005962941,0.007868055],"category_scores_gemma":[0.001465733,0.0006016739,0.0007855679,0.002131854,0.0004763365,0.001047109,0.001083481,0.001383765,0.01026074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000395502,"about_ca_system_score_gemma":0.0008146205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001097394,"about_ca_topic_score_gemma":0.001416724,"domain_scores_codex":[0.9996537,0.00003244715,0.00003002575,0.00006688737,0.0001848913,0.00003195965],"domain_scores_gemma":[0.9993117,0.0001649594,0.00006441625,0.0001222911,0.0003098985,0.00002675376],"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":[0.000075999,0.0000408588,0.0002984214,0.004225696,0.00007938995,0.0001628684,0.00009784109,0.0007358917,0.08175548,0.003312539,0.04301716,0.8661978],"study_design_scores_gemma":[0.00004107152,0.00009241198,0.003820828,0.0009572798,0.0001377478,0.002859775,0.0001182465,0.005056998,0.1802221,0.006071582,0.8005101,0.0001117192],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.01213341,0.214441,0.708648,0.00220978,0.002898047,0.001457725,0.009393692,0.01489127,0.03392714],"genre_scores_gemma":[0.03667011,0.260334,0.6495251,0.001050998,0.0008808508,0.00119897,0.02547092,0.002602088,0.02226694],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.007868055,"threshold_uncertainty_score":0.02632123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09799748196966657,"score_gpt":0.5434862319723243,"score_spread":0.4454887500026577,"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."}}