{"id":"W2886097787","doi":"10.1017/s1431927618011327","title":"Unravelling History Using Scanning Electron Microscopy","year":2018,"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":"University of Victoria","funders":"","keywords":"Scanning electron microscope; Materials science; Content (measure theory); Action (physics); Nanotechnology; Computer science; Physics; Composite material; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001964958,0.0003087233,0.0002880949,0.0001504711,0.0003830738,0.0000471331,0.0002471258,0.0001968481,0.0000635722],"category_scores_gemma":[0.00001429534,0.0003337941,0.0001442329,0.0002458565,0.000423179,0.00001255436,0.0001336254,0.0001689007,0.00001318975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001596081,"about_ca_system_score_gemma":0.0001392842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001405636,"about_ca_topic_score_gemma":0.00006310333,"domain_scores_codex":[0.9982318,0.00004435651,0.0003349986,0.0007414335,0.00008454641,0.000562884],"domain_scores_gemma":[0.9990468,0.000007552471,0.0001759583,0.0004948398,0.0001533609,0.0001214739],"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":[0.00005885339,0.00003460691,0.0006536834,0.0000109933,0.00008637755,6.544939e-7,0.00008328199,0.00001000861,0.9958404,0.00006433542,0.002587977,0.0005687768],"study_design_scores_gemma":[0.0001993987,0.0001658208,0.00004173905,0.0000186579,0.0001174283,0.00003020065,0.00004039869,0.0001657327,0.8383046,0.00007411277,0.1605231,0.0003187531],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.799953,0.008184221,0.1911886,0.00004584318,0.00007020443,0.0001746003,0.0000157564,0.00004665846,0.000321065],"genre_scores_gemma":[0.8938582,0.001419406,0.100182,0.0009488498,0.0004789554,0.00002852792,0.0001492356,0.00008782247,0.002846954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1579351,"threshold_uncertainty_score":0.9999114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01107889761695996,"score_gpt":0.3207102744094888,"score_spread":0.3096313767925289,"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."}}