{"id":"W2521806811","doi":"10.1111/jmi.12464","title":"Reverse Monte Carlo reconstruction algorithm for discrete electron tomography based on HAADF‐STEM atom counting","year":2016,"lang":"en","type":"article","venue":"Journal of Microscopy","topic":"Advanced Electron Microscopy Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University","funders":"","keywords":"Scanning transmission electron microscopy; Electron tomography; Tilt (camera); Monte Carlo method; Atom (system on chip); Electron; Dark field microscopy; Optics; Face (sociological concept); Transmission electron microscopy; Physics; Algorithm; Computational physics; Materials science; Computer science; Microscopy; Geometry; Mathematics","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":[0.001040888,0.0004485905,0.0006669873,0.0006302933,0.0006223444,0.0006455921,0.001668373,0.0009685023,0.003247605],"category_scores_gemma":[0.002386042,0.0004461854,0.0005311926,0.0004343692,0.0004909505,0.0007287019,0.0007475819,0.001125348,0.001149981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007040878,"about_ca_system_score_gemma":0.001174404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003604406,"about_ca_topic_score_gemma":0.004572065,"domain_scores_codex":[0.9996254,0.0001005002,0.00002226661,0.0000458742,0.0001732734,0.00003258401],"domain_scores_gemma":[0.9990672,0.0004818708,0.00007355258,0.0001270533,0.0002060751,0.00004420473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000405194,0.0001571446,0.001953592,0.0001833992,0.000118693,0.000228804,0.0002031685,0.6466372,0.02323243,0.06764131,0.003439974,0.2557991],"study_design_scores_gemma":[0.00001161541,0.00001125174,0.00005059677,0.000002832001,0.000003612036,0.00003873936,0.000004463197,0.9946316,0.002269856,0.002051707,0.000915813,0.000007900947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003631142,0.0000318906,0.9952088,0.00003971848,0.00001365166,0.00003042544,0.00002081486,0.0005252913,0.0004982292],"genre_scores_gemma":[0.05785635,0.00005130183,0.9407002,0.0000544615,0.00001083518,0.0001557949,0.0001202461,0.0001595366,0.0008913281],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003604406,"threshold_uncertainty_score":0.01086438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005003150220868193,"score_gpt":0.2903168010374446,"score_spread":0.2853136508165764,"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."}}