{"id":"W4304945794","doi":"10.1107/s2052252522009721","title":"Cryo-EM at ACA 2022","year":2022,"lang":"ko","type":"editorial","venue":"IUCrJ","topic":"Advanced Electron Microscopy Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute of General Medical Sciences","keywords":"Envelope (radar); Cryo-electron microscopy; Structural biology; Computer science; Data science; Computational biology; Nanotechnology; Political science; Chemistry; Biophysics; Biology; Materials science; Biochemistry; Telecommunications","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002241567,0.000606364,0.000487498,0.00007757654,0.0007614983,0.00005966369,0.001006392,0.001099267,0.003330401],"category_scores_gemma":[0.0001038282,0.0007073224,0.0003701764,0.0002480394,0.0001423624,0.000004610312,0.001445127,0.001171751,0.0001310062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004493354,"about_ca_system_score_gemma":0.0004530604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002304023,"about_ca_topic_score_gemma":0.00005430969,"domain_scores_codex":[0.9967613,0.000104872,0.0005152135,0.001341455,0.0004789392,0.0007981976],"domain_scores_gemma":[0.9978619,0.00005330557,0.0004061797,0.001340234,0.0001531438,0.0001852158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001053522,0.00008415859,0.000008509973,0.00003587154,0.00004845962,0.000005349516,0.0000296159,0.00001174903,0.3469202,0.00006596898,0.6509208,0.001764004],"study_design_scores_gemma":[0.0003454421,0.0005344434,0.000004646517,0.00001310013,0.00007343587,0.00001352344,0.00005312723,0.000003659436,0.155526,0.0002553837,0.8425537,0.000623494],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.06232496,0.0526337,0.0183464,0.002296259,0.8136621,0.006818572,0.01948162,0.0008206114,0.02361577],"genre_scores_gemma":[0.01155831,0.03519607,0.005149861,0.001142204,0.7012426,0.002754448,0.04056168,0.0006334761,0.2017613],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.1916329,"threshold_uncertainty_score":0.9995378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004369461345447669,"score_gpt":0.3101955553604642,"score_spread":0.3058260940150165,"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."}}