{"id":"W2951712999","doi":"10.48550/arxiv.cond-mat/0111045","title":"Mean-field approach to ferromagnetism in (III,Mn)V diluted magnetic semiconductors at low carrier densities","year":2001,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Magnetic Properties and Applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Materials Research; Natural Sciences and Engineering Research Council of Canada; Aspen Center for Physics; National Science Foundation","keywords":"Condensed matter physics; Magnetization; Ferromagnetism; Magnetic semiconductor; Impurity; Semiconductor; Magnetic field; Materials science; Metal–insulator transition; Metal; Physics; Quantum mechanics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004099579,0.0003973945,0.0008270079,0.0006447896,0.0006987563,0.0009256296,0.001399011,0.00104023,0.001661139],"category_scores_gemma":[0.0007577935,0.0002661971,0.000745551,0.0002735696,0.0009902098,0.0008695647,0.000514566,0.0005734712,0.0001560957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001245602,"about_ca_system_score_gemma":0.000593224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002979304,"about_ca_topic_score_gemma":0.00250344,"domain_scores_codex":[0.9998783,0.00003965057,0.000003639049,0.00001241262,0.00003555281,0.00003047508],"domain_scores_gemma":[0.9997674,0.0001172517,0.00003079462,0.00002316074,0.00003334896,0.00002806119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002082405,0.0001742495,0.001387939,0.0002096997,0.0000933445,0.0006921774,0.0001892414,0.4839225,0.02563375,0.481392,0.001118586,0.004978293],"study_design_scores_gemma":[0.00002669017,0.00003193834,0.0002181965,0.000005394872,0.00000995647,0.00005468659,0.00001282826,0.9470415,0.0009692884,0.05132454,0.0002949917,0.000009921589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8227409,0.002336661,0.1513054,0.001907227,0.0001599511,0.00008117345,0.0001862983,0.0002036285,0.02107876],"genre_scores_gemma":[0.9811817,0.0006149574,0.01248017,0.000165305,0.00009160299,0.00007557603,0.00007216669,0.00003623077,0.005282286],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002979304,"threshold_uncertainty_score":0.009037495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05004236540972327,"score_gpt":0.1802171516042085,"score_spread":0.1301747861944852,"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."}}