{"id":"W2886912447","doi":"10.1016/j.mtla.2018.06.012","title":"Nucleation and growth of <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si2.gif\" overflow=\"scroll\"> <mml:mrow> <mml:mo>{</mml:mo> <mml:mn>11</mml:mn> <mml:mover accent=\"true\"> <mml:mn>2</mml:mn> <mml:mo>¯</mml:mo> </mml:mover> <mml:mn>2</mml:mn> <mml:mo>}</mml:mo> </mml:mrow> </mml:math> twins in titanium: Elastic energy and stress fields at the vicinity of twins","year":2018,"lang":"lv","type":"article","venue":"Materialia","topic":"Microstructure and mechanical properties","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Scroll; Computer science; Materials science; Artificial intelligence; Archaeology; History","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":[0.0001193351,0.0001601153,0.0001791477,0.0003520403,0.0005619617,0.0009396014,0.0005823625,0.0004338707,0.006394726],"category_scores_gemma":[0.0005258429,0.000349902,0.0002809118,0.0002057558,0.0002869118,0.0004363658,0.00030579,0.000441818,0.00102616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001120339,"about_ca_system_score_gemma":0.0005732712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006731216,"about_ca_topic_score_gemma":0.009464147,"domain_scores_codex":[0.9998159,0.000005706367,0.000006847967,0.00004751192,0.00007165285,0.00005249524],"domain_scores_gemma":[0.9998586,0.00002722181,0.00001883046,0.00001769601,0.00005109115,0.00002649422],"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":[0.0004389691,0.0001079235,0.003269344,0.0001920712,0.00002416489,0.0004296052,0.0005657818,0.004922276,0.9458728,0.02965957,0.004786848,0.009730685],"study_design_scores_gemma":[0.00003867564,0.0001664406,0.01307629,0.00001925225,0.00001994485,0.0001903422,0.0003877177,0.02329206,0.9518588,0.00199058,0.008922177,0.00003759402],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9504426,0.0006325074,0.006753644,0.0002273526,0.0001495461,0.0000496974,0.00121747,0.0001661132,0.04036106],"genre_scores_gemma":[0.9863538,0.0001609406,0.001652899,0.00002132859,0.00001141132,0.00002710929,0.0007345511,0.00007967102,0.01095834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006731216,"threshold_uncertainty_score":0.02139246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01603170128724178,"score_gpt":0.2304699389658632,"score_spread":0.2144382376786214,"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."}}