{"id":"W4379619169","doi":"10.1016/j.micron.2023.103499","title":"Peltier cooling for the reduction of carbon contamination in scanning electron microscopy","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 New Brunswick; Hitachi (Canada); University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Scanning electron microscope; Contamination; Materials science; Carbon fibers; Cathode ray; Liquid nitrogen; Electron beam processing; Electron microscope; Microscopy; Electron; Analytical Chemistry (journal); Optoelectronics; Optics; Chemistry; Composite material; Environmental chemistry; Physics","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":[0.0001653264,0.00007040837,0.00007287135,0.00004857411,0.00005874611,0.000005896288,0.00009139942,0.00006695924,6.512647e-7],"category_scores_gemma":[0.00001513943,0.000064064,0.00003577025,0.0001722515,0.00003883805,0.000002228761,0.00002315901,0.00005871013,4.800922e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003084426,"about_ca_system_score_gemma":0.00002989601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004408435,"about_ca_topic_score_gemma":0.00002831983,"domain_scores_codex":[0.9994585,0.00001200359,0.0001431235,0.0001718142,0.00003252321,0.0001820616],"domain_scores_gemma":[0.999709,0.00001144833,0.00007048256,0.0001513372,0.0000479987,0.000009712402],"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":[0.00005948811,0.00001125304,0.0001513166,0.00001047916,0.000005397476,3.408644e-8,0.00004968071,0.0002202574,0.9970905,0.00006285973,0.0006045033,0.001734223],"study_design_scores_gemma":[0.0002052024,0.0001108061,0.0007312274,0.00001230251,0.000007267398,0.000002291339,0.00008785356,0.0003477049,0.9858527,0.00009782337,0.01247755,0.00006722661],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839136,0.0007358836,0.01465387,0.0001650283,0.00004051702,0.0004213506,0.000008165553,0.00001896408,0.00004260969],"genre_scores_gemma":[0.9973102,0.0004160813,0.001373899,0.00002219858,0.0000695618,0.0001553453,0.0001349216,0.00001741352,0.0005004054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01339656,"threshold_uncertainty_score":0.2612454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008405522580750646,"score_gpt":0.3331326604655508,"score_spread":0.3247271378848001,"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."}}