{"id":"W2001459688","doi":"10.1063/1.2826946","title":"Energy-based quasi-static modeling of the actuation and sensing behavior of single-crystal iron-gallium alloys","year":2008,"lang":"en","type":"article","venue":"Journal of Applied Physics","topic":"Magnetic Properties and Applications","field":"Materials Science","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; Queen's University","funders":"Office of Naval Research; Multidisciplinary University Research Initiative; Defense Advanced Research Projects Agency","keywords":"Magnetostriction; Transducer; Materials science; Actuator; Magnetic field; Magnetic reluctance; Stress (linguistics); Energy (signal processing); Condensed matter physics; Mechanical engineering; Mechanics; Acoustics; Engineering; Electrical engineering; Physics; Magnet","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":[],"consensus_categories":[],"category_scores_codex":[0.0001275533,0.00008131629,0.0001887918,0.00002049761,0.0000870514,0.0000120684,0.0001220713,0.00002793255,0.000009795893],"category_scores_gemma":[0.000006569036,0.00005617494,0.00005782496,0.0000833684,0.0001266845,0.00005692137,0.00003182853,0.00006259715,3.141107e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001890982,"about_ca_system_score_gemma":0.0000956791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002882348,"about_ca_topic_score_gemma":0.000002151905,"domain_scores_codex":[0.9991305,0.00001646555,0.0003882046,0.00008077142,0.0002893855,0.00009470569],"domain_scores_gemma":[0.9991441,0.00004266264,0.0004851239,0.0001505721,0.0001421558,0.00003536526],"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":[0.0000430758,0.0001539686,0.000009800755,0.00002599866,0.000002999967,3.599544e-7,0.0004228918,0.04390854,0.9526359,0.0004841876,0.0000124353,0.002299834],"study_design_scores_gemma":[0.0004724331,0.0001359007,0.00006617637,0.00005373485,0.00009091985,0.00001339229,0.0002346637,0.2574742,0.7391477,0.002178822,0.00003367434,0.00009846251],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9179689,0.00002124975,0.08160933,0.00004369433,0.0000407112,0.00008038127,0.000005661853,0.000003377937,0.0002266685],"genre_scores_gemma":[0.9915413,0.000009465217,0.008320089,0.00004551853,0.00006448855,0.000002046954,9.407941e-7,0.000009635531,0.000006504902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2135656,"threshold_uncertainty_score":0.2290748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03122961549286925,"score_gpt":0.2211820452187946,"score_spread":0.1899524297259254,"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."}}