{"id":"W2350369588","doi":"10.1016/j.scriptamat.2016.04.026","title":"Modeling discrete twin lamellae in a microstructural framework","year":2016,"lang":"en","type":"article","venue":"Scripta Materialia","topic":"Magnesium Alloys: Properties and Applications","field":"Materials Science","cited_by":75,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Los Alamos National Laboratory; Laboratory Directed Research and Development; National Science Foundation","keywords":"Materials science; Crystal twinning; Perspective (graphical); Deformation (meteorology); Microstructure; Computer science; Metallurgy; Composite material; Artificial intelligence","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002444813,0.0001908332,0.0002263153,0.00005395547,0.0001064812,0.0002271066,0.0004211187,0.0001112801,0.003801819],"category_scores_gemma":[0.00005529707,0.0001188823,0.00004542933,0.0001083308,0.0001018004,0.0002783171,0.0001779682,0.00005834322,0.0007533492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005879897,"about_ca_system_score_gemma":0.00003002585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007362969,"about_ca_topic_score_gemma":0.00005902709,"domain_scores_codex":[0.9984799,0.00007143435,0.0003909554,0.0004327472,0.0001670745,0.0004578994],"domain_scores_gemma":[0.9993248,0.000003312043,0.00006055075,0.0004840954,0.00004074498,0.00008649869],"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":[0.00005951868,0.00000963692,0.0001663345,0.00002276774,0.000001295624,0.000002825795,0.0001853303,0.000002793284,0.9904221,0.006880807,0.002022732,0.0002238438],"study_design_scores_gemma":[0.001270981,0.0001017073,0.001997793,0.0004241643,0.00002469052,0.00002512814,0.0003852799,0.001663439,0.9076788,0.03944878,0.04596863,0.001010579],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858534,0.0000692254,0.002399062,0.001687964,0.009177212,0.0002537678,0.00009847379,0.0001155906,0.0003453603],"genre_scores_gemma":[0.9863429,0.00001569429,0.005607621,0.0002449385,0.0002905628,0.00008045308,0.000005241586,0.0000298274,0.007382737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08274327,"threshold_uncertainty_score":0.9971088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01924356821012705,"score_gpt":0.2508246251784422,"score_spread":0.2315810569683152,"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."}}