{"id":"W4408918951","doi":"10.1142/s0219455426502597","title":"Bi-Mode Electromagnetic Energy Harvester and Energy Management Strategy for Long-Time Monitoring Sensor","year":2025,"lang":"en","type":"article","venue":"International Journal of Structural Stability and Dynamics","topic":"Innovative Energy Harvesting Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"National Natural Science Foundation of China","keywords":"Mode (computer interface); Energy (signal processing); Energy harvesting; Energy management; Acoustics; Electrical engineering; Computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009529066,0.0001458567,0.0001741368,0.0002068233,0.00004907837,0.000143229,0.0002045666,0.00007429947,0.000004024935],"category_scores_gemma":[0.00004036524,0.0001316015,0.00004208998,0.0001031961,0.00009498552,0.0003043457,0.00007522056,0.0001224951,3.373554e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002016047,"about_ca_system_score_gemma":0.00001472002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002191458,"about_ca_topic_score_gemma":0.00004274999,"domain_scores_codex":[0.9991995,0.00001600414,0.0003494195,0.0001315155,0.0001484228,0.0001551704],"domain_scores_gemma":[0.9994361,0.0001025397,0.00008917272,0.00008257237,0.0002608247,0.00002877723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003504191,0.00004213719,0.05011068,0.0003279359,0.001446273,0.0000709821,0.00009260423,0.02820365,0.01854472,0.4634842,0.00006619118,0.4372602],"study_design_scores_gemma":[0.00265043,0.0005109977,0.3073497,0.0004193961,0.0001523938,0.0003180862,0.0004232513,0.5014188,0.03730437,0.1476798,0.000994964,0.0007778317],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9460974,0.000348412,0.05242053,0.0002158691,0.0005004581,0.000031556,0.00002241677,0.00005762252,0.000305725],"genre_scores_gemma":[0.9919042,0.0001742096,0.007518058,0.00001809097,0.00007267475,0.000004539252,0.000009061574,0.00001083759,0.0002883284],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4732152,"threshold_uncertainty_score":0.5366552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008476280103890678,"score_gpt":0.2474970022209357,"score_spread":0.239020722117045,"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."}}