{"id":"W2092529999","doi":"10.1007/s11661-003-1003-2","title":"On the precipitation-hardening behavior of the Al−Mg−Si−Cu alloy AA6111","year":2003,"lang":"en","type":"article","venue":"Metallurgical and Materials Transactions A","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":206,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Alloy; Microstructure; Materials science; Differential scanning calorimetry; Precipitation; Nucleation; Precipitation hardening; Transmission electron microscopy; Isothermal process; Hardening (computing); Volume fraction; Metallurgy; Phase (matter); Thermodynamics; Composite material; Chemistry; Nanotechnology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001754703,0.0001375209,0.0001814833,0.00002259494,0.0001579772,0.00006629359,0.0001113676,0.00006041134,0.001819829],"category_scores_gemma":[0.00001852293,0.00007695023,0.00007537488,0.0000832224,0.0001239575,0.00006614602,0.000005154922,0.0001099144,0.00001190524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001283376,"about_ca_system_score_gemma":0.000008959739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002740282,"about_ca_topic_score_gemma":0.00002069751,"domain_scores_codex":[0.99925,0.00009599521,0.0002453921,0.0001284764,0.0001317988,0.0001483214],"domain_scores_gemma":[0.9996625,0.00007006165,0.00003311257,0.0001756535,0.00002584483,0.00003287356],"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":[0.00001882167,0.00003985774,0.000003172714,0.00003979989,0.0000938533,0.000001801896,0.0004565984,0.003669404,0.9928712,0.002398519,0.00007918647,0.000327842],"study_design_scores_gemma":[0.0007152783,0.00009267954,0.003237322,0.00009180755,0.0003797343,0.0001532733,0.0002952017,0.0007446907,0.9661848,0.0008809241,0.02679388,0.0004304173],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928399,0.0001501938,0.005534406,0.0001432685,0.0005734044,0.0003042447,0.00003149568,0.00005985747,0.0003632585],"genre_scores_gemma":[0.9988215,0.00006597729,0.0004558688,0.00006400317,0.00001220004,0.0001016266,0.000001619566,0.00002297438,0.000454226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02671469,"threshold_uncertainty_score":0.9990926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01065394930069827,"score_gpt":0.1950276766433767,"score_spread":0.1843737273426784,"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."}}