{"id":"W4385071896","doi":"10.1093/micmic/ozad067.493","title":"High-Throughput Low-Dose Biomolecule Imaging in Liquid Phase Electron Microscopy","year":2023,"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":"McMaster University; University of Waterloo","funders":"","keywords":"Biomolecule; Throughput; Materials science; Phase imaging; Electron microscope; Microscopy; Phase (matter); Liquid phase; Biological specimen; Nanotechnology; Optics; Chemistry; Physics; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006529307,0.0004635873,0.0005466622,0.0005993624,0.0003083284,0.0009584305,0.0009658774,0.0008001831,0.002828445],"category_scores_gemma":[0.000558175,0.0004124583,0.0002451822,0.0004955371,0.0003681258,0.00104314,0.0006209576,0.001233864,0.00232027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00049202,"about_ca_system_score_gemma":0.0002116344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000349756,"about_ca_topic_score_gemma":0.0009181988,"domain_scores_codex":[0.9996557,0.00006094975,0.00001649837,0.00006407149,0.0001717257,0.00003104317],"domain_scores_gemma":[0.999662,0.0001487807,0.00003801627,0.00006966243,0.00005784363,0.0000237036],"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":[0.00004888987,0.00005842742,0.0002558355,0.0001628912,0.000007734388,0.0001236871,0.00002923987,0.0005609586,0.9872102,0.0007417057,0.000703485,0.01009702],"study_design_scores_gemma":[0.00001630527,0.0001151141,0.001232021,0.00003241948,0.00001116834,0.0002982102,0.00002422965,0.01527402,0.9750845,0.0004174542,0.007477685,0.00001685425],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3190372,0.006663507,0.6501818,0.0007884835,0.0002025765,0.0009662557,0.002111908,0.006982467,0.01306581],"genre_scores_gemma":[0.4271479,0.002992146,0.5620278,0.0002068535,0.0000827961,0.0005927354,0.001331627,0.0003634315,0.005254738],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002828445,"threshold_uncertainty_score":0.009462118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005100999166971429,"score_gpt":0.3370840943546851,"score_spread":0.3319830951877136,"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."}}