{"id":"W4388451400","doi":"10.1016/j.micron.2023.103562","title":"Sample thickness affects contrast and measured shape in TEM images and in electron tomograms","year":2023,"lang":"en","type":"article","venue":"Micron","topic":"Advanced Electron Microscopy Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; National Institute for Nanotechnology","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Electron tomography; Materials science; Aspect ratio (aeronautics); Transmission electron microscopy; Tomography; Optics; Contrast (vision); Matrix (chemical analysis); Electron; Morphology (biology); Image contrast; Contrast ratio; Scanning transmission electron microscopy; Nanotechnology; Optoelectronics; Physics; Composite material","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001398553,0.00009951546,0.0001069231,0.00005280935,0.00003668027,0.0000177716,0.00005876021,0.00009080659,0.000001658587],"category_scores_gemma":[0.00002213797,0.0001024107,0.00001373634,0.0001587986,0.00005132983,0.000003800438,0.00005163955,0.00009518764,0.000001069849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001540841,"about_ca_system_score_gemma":0.00001623929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006235172,"about_ca_topic_score_gemma":0.0004000105,"domain_scores_codex":[0.999331,0.00002448225,0.00009063227,0.000269912,0.00003199347,0.0002519878],"domain_scores_gemma":[0.9998034,0.0000166684,0.0000245124,0.0001140574,0.00001237051,0.00002896354],"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":[0.00003172589,0.00001709104,0.004344173,0.00001310987,0.000002692932,0.000001118287,0.00001947708,0.000003178595,0.9892064,0.00003462083,0.0003780518,0.005948319],"study_design_scores_gemma":[0.0004008954,0.0001042284,0.02290928,0.00001802843,0.000002886848,0.000009003404,0.00002894056,0.00006460657,0.9690256,0.0003223602,0.006977936,0.0001362081],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959661,0.001615557,0.001852122,0.0002130204,0.000006652771,0.0002582674,0.00001667831,0.00002997452,0.00004161083],"genre_scores_gemma":[0.9973447,0.001166755,0.001133473,0.00007875051,0.0000183661,0.00007446983,0.00009696774,0.00001562347,0.00007087117],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02018082,"threshold_uncertainty_score":0.4176188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006989747526019103,"score_gpt":0.2912824263562547,"score_spread":0.2842926788302356,"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."}}