{"id":"W2130322281","doi":"10.1017/s143192761200150x","title":"Contribution of a New Generation Field-Emission Scanning Electron Microscope in the Understanding of a 2099 Al-Li Alloy","year":2012,"lang":"en","type":"article","venue":"Microscopy and Microanalysis","topic":"Electron and X-Ray Spectroscopy Techniques","field":"Materials Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; McGill University","funders":"Hydro-Québec; Alcoa","keywords":"Materials science; Scanning electron microscope; Microstructure; Alloy; Field emission gun; Scanning transmission electron microscopy; Characterization (materials science); Transmission electron microscopy; Texture (cosmology); Microanalysis; Grain boundary; Lithium (medication); Field emission microscopy; Metallurgy; Nanotechnology; Diffraction; Composite material; Optics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001943404,0.0001608464,0.0001214292,0.0005059933,0.0001858915,0.0003117331,0.0002894317,0.0005231455,0.001305857],"category_scores_gemma":[0.0001982434,0.0001482832,0.0001600513,0.0001080347,0.0002580957,0.0008105622,0.0001891851,0.000452653,0.0004122776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002085191,"about_ca_system_score_gemma":0.0001704239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004636127,"about_ca_topic_score_gemma":0.000956062,"domain_scores_codex":[0.9999471,0.000009513169,0.000003937742,0.00001167748,0.00002312261,0.000004657972],"domain_scores_gemma":[0.9998958,0.0000341856,0.000008230876,0.00001775052,0.00003490969,0.000009109794],"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":[0.00008710571,0.00002597808,0.001278958,0.0001222918,0.000007827419,0.0004579735,0.00004518119,0.0006674046,0.9682758,0.003620862,0.0003598213,0.02505073],"study_design_scores_gemma":[0.00002147815,0.0002722918,0.01685277,0.00009300601,0.00004586295,0.008547366,0.0003059124,0.05291906,0.857859,0.007425265,0.05561063,0.00004730454],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5731357,0.02151601,0.3739579,0.001702844,0.0004040229,0.0001157331,0.0005606537,0.001371126,0.02723596],"genre_scores_gemma":[0.706108,0.006659023,0.2779483,0.0003602608,0.0001302458,0.00004046307,0.0002910237,0.00008446227,0.008378166],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001305857,"threshold_uncertainty_score":0.004368484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02147923353065469,"score_gpt":0.3094956672875155,"score_spread":0.2880164337568608,"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."}}