{"id":"W4252106318","doi":"10.1002/9783527808465.emc2016.6495","title":"Automatic <scp>FIB‐SEM</scp> Preparation of Straight Pillars for In‐Situ Nanoindentation","year":2016,"lang":"en","type":"other","venue":"European Microscopy Congress 2016: Proceedings","topic":"Force Microscopy Techniques and Applications","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fibics (Canada)","funders":"","keywords":"Focused ion beam; Materials science; Nanoindentation; Micrometer; Composite material; Perpendicular; Sample preparation; Indentation; Deformation (meteorology); Displacement (psychology); Geometry; Mechanical engineering; Ion","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":[0.0006836571,0.001069888,0.0007336285,0.000684606,0.0005613278,0.0006058721,0.001003926,0.0006572251,0.007805431],"category_scores_gemma":[0.0008803634,0.000494673,0.0003019675,0.0005038605,0.0004258432,0.0005288644,0.0006483924,0.0008751036,0.004105953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002733128,"about_ca_system_score_gemma":0.0003045143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004425448,"about_ca_topic_score_gemma":0.001079115,"domain_scores_codex":[0.9994357,0.00004387356,0.00005965466,0.0001192036,0.0002621743,0.00007925262],"domain_scores_gemma":[0.9989397,0.0002925844,0.0001014327,0.000402813,0.0002332539,0.0000302206],"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":[0.00006075237,0.0000381189,0.0001841718,0.0002590363,0.00001255353,0.00009554344,0.00006393706,0.0002971599,0.9860587,0.0003940517,0.002163935,0.01037203],"study_design_scores_gemma":[0.00001264135,0.0001197205,0.001695534,0.00001314997,0.000006572624,0.0001646805,0.00002333253,0.004114545,0.9861001,0.0001094953,0.007615435,0.00002462306],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5625998,0.00220272,0.3904741,0.0003374438,0.0004601614,0.001884525,0.0101343,0.01650609,0.01540092],"genre_scores_gemma":[0.5773795,0.001227982,0.4055334,0.0002948736,0.00009051034,0.002148309,0.006285717,0.002241975,0.004797635],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.007805431,"threshold_uncertainty_score":0.02611178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007800815970904582,"score_gpt":0.3012712126640038,"score_spread":0.2934703966930992,"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."}}