{"id":"W2023662271","doi":"10.1016/s0921-5093(03)00530-6","title":"Sub-micrometer structures generated during dry machining of copper","year":2003,"lang":"en","type":"article","venue":"Materials Science and Engineering A","topic":"Microstructure and mechanical properties","field":"Materials Science","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"General Motors (Canada); Natural Sciences and Engineering Research Council; University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Equiaxed crystals; Materials science; Microstructure; Nucleation; Transmission electron microscopy; Dislocation; Indentation hardness; Copper; Composite material; Machining; Recrystallization (geology); Annealing (glass); Grain size; Micrometer; Metallurgy; Nanotechnology; Optics","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":[],"consensus_categories":[],"category_scores_codex":[0.000681567,0.0001541859,0.0002377087,0.0001278497,0.0001618444,0.0001695411,0.000197112,0.00005378546,0.0002067974],"category_scores_gemma":[0.0002129058,0.0001171029,0.00001703796,0.0002149565,0.0001866837,0.0002514724,0.0000850077,0.00005264606,0.000009058748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002705488,"about_ca_system_score_gemma":0.00005510876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000280982,"about_ca_topic_score_gemma":7.143584e-7,"domain_scores_codex":[0.9987919,0.00002734533,0.0002659787,0.0003048765,0.000240282,0.0003695587],"domain_scores_gemma":[0.9995528,0.00001379183,0.00006178792,0.0001902324,0.00008816141,0.00009326784],"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":[0.00001034644,0.000003578795,0.00002446694,0.00007623846,0.000002177173,0.000002043601,0.0001806932,0.000189351,0.9985295,0.000930422,0.000009325273,0.00004183476],"study_design_scores_gemma":[0.0001675654,0.00002989919,0.0009543741,0.00003159108,0.00000649436,0.0000285339,0.00002868462,0.00004836074,0.9983328,0.00009613301,0.000118899,0.0001566609],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987529,0.0001983746,0.0001070622,0.000008504762,0.0007149256,0.00008363916,0.00001460579,0.00005716997,0.00006283999],"genre_scores_gemma":[0.996609,0.00001804671,0.003258202,0.00003518562,0.00003835356,0.000004898402,9.194584e-7,0.00001463492,0.0000207947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00315114,"threshold_uncertainty_score":0.4775318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008501671081245873,"score_gpt":0.1953624800945069,"score_spread":0.186860809013261,"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."}}