{"id":"W7132981572","doi":"","title":"Imaging of Non-conducting Beam Sensitive Materials using Scanning Electron Microscopy: Practical Applications of ESEM and LVSEM","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Electron and X-Ray Spectroscopy Techniques","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; University of Toronto; Strong; Compute Canada","keywords":"Characterization (materials science); Environmental scanning electron microscope; Scanning electron microscope; Microplastics; Beam (structure); Face (sociological concept)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001904154,0.0007142816,0.001497135,0.0005621498,0.0007148705,0.0002152781,0.0003765396,0.000291061,0.0006120701],"category_scores_gemma":[0.0002273151,0.0008476128,0.0001543835,0.0007964289,0.0004461753,0.0004953645,0.0002875804,0.0007683431,0.00000340888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004345675,"about_ca_system_score_gemma":0.001070508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00314817,"about_ca_topic_score_gemma":0.00004483624,"domain_scores_codex":[0.995286,0.0004304171,0.001356014,0.001223179,0.0006979429,0.001006383],"domain_scores_gemma":[0.9955247,0.0003598913,0.002735856,0.0006616699,0.0005608193,0.0001570759],"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":[0.0003791823,0.0001741798,0.0001213615,0.0008297011,0.00007316533,0.000008266427,0.01025942,0.00001807253,0.9874678,0.0004940802,0.00004444038,0.0001303149],"study_design_scores_gemma":[0.0003162566,0.0003809372,0.0001277391,0.0005647306,0.0004212592,0.0001159999,0.02462558,0.0003039538,0.9723108,0.0001474165,0.00006316847,0.0006221543],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9856826,0.0008719008,0.0103006,0.0001462377,0.0003522901,0.001820439,0.00008716861,0.0001013767,0.000637384],"genre_scores_gemma":[0.9575483,0.000341238,0.04092677,0.00004271279,0.0001605071,0.0001695033,0.0002158355,0.0001443383,0.0004507656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03062617,"threshold_uncertainty_score":0.9993975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02272238891007523,"score_gpt":0.4102412862402221,"score_spread":0.3875188973301469,"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."}}