{"id":"W1988534267","doi":"10.1109/tmag.2012.2199289","title":"A Magnetoelectric Generator for Energy Harvesting From the Vibration of Magnetic Levitation","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","topic":"Innovative Energy Harvesting Technologies","field":"Engineering","cited_by":111,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Magnetostriction; Energy harvesting; Vibration; Levitation; Materials science; Magnetic levitation; Acoustics; Mechanical energy; Generator (circuit theory); Electric generator; Energy transformation; Magnetic field; Power (physics); Electrical engineering; Physics; Magnet; Engineering","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":[0.0001418395,0.0001862716,0.0001519639,0.0001490369,0.0001283311,0.00003125371,0.0001845789,0.0001289012,0.0000479456],"category_scores_gemma":[0.00005197618,0.0001651478,0.00006292791,0.0005701826,0.00007691444,0.0001784661,0.000001310389,0.0001654185,0.000005438962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005126892,"about_ca_system_score_gemma":0.00001990442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006275502,"about_ca_topic_score_gemma":0.00005691056,"domain_scores_codex":[0.9990439,0.00004327135,0.0003265203,0.000135997,0.0001556461,0.0002946716],"domain_scores_gemma":[0.9990147,0.0004839741,0.00006791282,0.0002832982,0.0001163975,0.00003369302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002823528,0.0001141439,0.00007729753,0.00004956521,0.00005441699,3.112364e-7,0.0003778014,0.1308636,0.3262857,0.003834621,0.001076955,0.5372373],"study_design_scores_gemma":[0.0005049605,0.000415969,0.002394008,0.0000408846,0.0001126546,0.000003219536,0.0001163171,0.1288709,0.8616754,0.000917771,0.004600334,0.0003475753],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1138146,0.0007908602,0.8837973,0.00009986708,0.0006648953,0.0001805539,0.00007742103,0.0003646085,0.0002099088],"genre_scores_gemma":[0.9545217,0.00008453396,0.04469173,0.000082631,0.0001477472,0.0001596979,0.00001631853,0.00004968877,0.000245945],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8407071,"threshold_uncertainty_score":0.673453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0203231548152503,"score_gpt":0.2144400601128364,"score_spread":0.1941169052975861,"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."}}