{"id":"W2208038589","doi":"10.4236/jamp.2015.38120","title":"Generalized Dynamic Modeling of Iron-Gallium Alloy (Galfenol) for Transducers","year":2015,"lang":"en","type":"article","venue":"Journal of Applied Mathematics and Physics","topic":"Magnetic Properties and Applications","field":"Materials Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"STMicroelectronics (Canada); University of Toronto","funders":"","keywords":"Materials science; Alloy; Rod; Gallium; Excitation; Transducer; Strain (injury); Mechanics; Structural engineering; Metallurgy; Acoustics; Engineering; Electrical engineering; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001362633,0.0004949831,0.0004351356,0.0002891225,0.0001840441,0.0004461097,0.0006586525,0.0007217148,0.0009972246],"category_scores_gemma":[0.000213558,0.0001945534,0.0004573421,0.0002063302,0.0003235463,0.0004896958,0.0003161474,0.0002588042,0.0002237694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004033014,"about_ca_system_score_gemma":0.0003228939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002640401,"about_ca_topic_score_gemma":0.003075392,"domain_scores_codex":[0.9998941,0.00002231527,0.000004294529,0.00002818972,0.00004181452,0.000009241454],"domain_scores_gemma":[0.9999497,0.00001716792,0.00001181799,0.000005604799,0.00001261863,0.000003068518],"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":[0.00003105587,0.00001316717,0.000410393,0.0001043148,0.00002149533,0.00018953,0.00008886907,0.9502998,0.02380143,0.01151798,0.0002693359,0.01325263],"study_design_scores_gemma":[0.000001476381,0.00001713893,0.0001363099,0.000004218278,0.000004557246,0.00002914904,0.000008060224,0.9966677,0.001173401,0.0008229093,0.00113122,0.000003880276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06952376,0.001019185,0.9163228,0.0002371537,0.00006646157,0.00005096544,0.0001167054,0.0002644038,0.0123987],"genre_scores_gemma":[0.9507154,0.0007868424,0.03536637,0.00007399349,0.00001787805,0.0001185261,0.0001617328,0.00005240543,0.01270683],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002640401,"threshold_uncertainty_score":0.005250096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03782193504357401,"score_gpt":0.259851732770647,"score_spread":0.222029797727073,"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."}}