{"id":"W4409716940","doi":"10.1016/j.jmmm.2025.173085","title":"Analysis of Microstructural, Electronic and Magnetic Properties of Nanocrystalline Compound Sm2ZrCo16: Effects of Annealing Temperature and Role of Intergranular Exchange Coupling","year":2025,"lang":"en","type":"article","venue":"Journal of Magnetism and Magnetic Materials","topic":"Magnetic Properties of Alloys","field":"Materials Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Ontario Ministry of Research, Innovation and Science; Agence Universitaire de la Francophonie; Ministère de l’Enseignement Supérieur et de la Recherche Scientifique","keywords":"Nanocrystalline material; Materials science; Intergranular corrosion; Annealing (glass); Coupling (piping); Condensed matter physics; Inductive coupling; Nuclear magnetic resonance; Microstructure; Nanotechnology; Metallurgy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009726529,0.0003388778,0.001646992,0.0006473916,0.0000632675,0.00008341432,0.0003576599,0.0001756629,0.0003587008],"category_scores_gemma":[0.00020177,0.0002602218,0.0001239317,0.0003575674,0.0007741415,0.0001864673,0.0003029645,0.0001359268,1.356164e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001734124,"about_ca_system_score_gemma":0.0001122607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003731803,"about_ca_topic_score_gemma":0.00004123561,"domain_scores_codex":[0.9970492,0.0001993727,0.001677579,0.0003251058,0.0003829744,0.0003657364],"domain_scores_gemma":[0.9977897,0.0001694979,0.001145461,0.0003204568,0.0004725228,0.0001023071],"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":[0.0007124083,0.00007895238,0.0004117642,0.004941901,0.0001582248,0.000006653684,0.0008327977,0.00003871403,0.9908546,0.0001206253,0.00002199118,0.001821342],"study_design_scores_gemma":[0.001765456,0.00315203,0.009872036,0.001300486,0.001613397,0.00006338234,0.0003840302,0.0002481759,0.9809176,0.0003423735,0.0001201134,0.0002208909],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8780885,0.1210793,0.00001053674,0.0001009569,0.0002251886,0.0003988131,0.0000674211,0.00000665687,0.00002264518],"genre_scores_gemma":[0.9911985,0.007542739,0.001031483,0.00002842899,0.00003579205,0.000006876262,0.000004321929,0.00001982779,0.0001320409],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1135365,"threshold_uncertainty_score":0.999985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002735736639693899,"score_gpt":0.188587257771899,"score_spread":0.1858515211322051,"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."}}