{"id":"W2112135141","doi":"10.1017/s1431927604882229","title":"Characterization of Intergranular Fracture Surfaces in a Ni-Cr-Fe Alloy using SEM, FIB and AEM Techniques","year":2004,"lang":"en","type":"article","venue":"Microscopy and Microanalysis","topic":"Metal and Thin Film Mechanics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fibics (Canada)","funders":"","keywords":"Materials science; Intergranular corrosion; Characterization (materials science); Alloy; Metallurgy; Intergranular fracture; Fracture (geology); Composite material; Nanotechnology","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":[],"consensus_categories":[],"category_scores_codex":[0.0001570588,0.0001685872,0.000340391,0.0002041592,0.0000389723,0.00003832709,0.00007251814,0.0001254567,0.00001484484],"category_scores_gemma":[0.000006214107,0.0001590118,0.00005417561,0.0002795568,0.00003555317,0.0001462617,0.00003783294,0.0001302168,7.95931e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003212609,"about_ca_system_score_gemma":0.00001045233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002647582,"about_ca_topic_score_gemma":0.00009687175,"domain_scores_codex":[0.999281,0.00002177737,0.0002867559,0.0001904848,0.00006489141,0.0001550355],"domain_scores_gemma":[0.9997319,0.00000533437,0.00006364425,0.0001317352,0.00002759562,0.00003979757],"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":[0.000009282953,0.00001886386,0.0006231098,0.0001251494,0.00006995782,0.000003521957,0.0004971374,0.0001982919,0.9977717,0.00001679033,0.000004453574,0.0006616869],"study_design_scores_gemma":[0.0002019603,0.00001956669,0.0005030174,0.0001381687,0.0001097598,0.000009535681,0.00005448389,0.002929571,0.9949094,0.0001909493,0.0007699093,0.0001636971],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861792,0.001312942,0.01221682,0.00003171325,0.00006622988,0.0001052215,0.00002693778,0.00004950365,0.00001146856],"genre_scores_gemma":[0.9917468,0.0009999193,0.007070749,0.00005675006,0.00001348889,0.000003028267,0.00004023907,0.00002047622,0.00004859501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00556759,"threshold_uncertainty_score":0.6484312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006466131706323624,"score_gpt":0.2205099062480809,"score_spread":0.2140437745417573,"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."}}