{"id":"W7117578173","doi":"10.18280/ts.420612","title":"Low-Power Signal Sensing and Neural Compression Transmission Collaborative Optimization Methods for Edge Intelligence","year":2025,"lang":"","type":"article","venue":"Traitement du signal","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Enhanced Data Rates for GSM Evolution; Artificial neural network; SIGNAL (programming language); Transmission (telecommunications); Data compression; Compression (physics); Pattern recognition (psychology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0008244177,0.0005621669,0.0006091683,0.0002619105,0.0002977103,0.0008281585,0.0008083751,0.0009133967,0.00206945],"category_scores_gemma":[0.003127819,0.0002713318,0.0003151372,0.0005091703,0.0009205271,0.001580057,0.001040755,0.0009854039,0.0002507078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004247653,"about_ca_system_score_gemma":0.0003586138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001237759,"about_ca_topic_score_gemma":0.001364863,"domain_scores_codex":[0.999739,0.00009665749,0.00001450669,0.00004866208,0.00008284379,0.00001827054],"domain_scores_gemma":[0.9991143,0.000635097,0.00006144689,0.00005668619,0.0001152774,0.00001707048],"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":[0.0001427173,0.00006405384,0.0003210521,0.0001686855,0.00005535289,0.00007580562,0.0001181917,0.8073047,0.007537482,0.07760235,0.001764923,0.1048447],"study_design_scores_gemma":[0.000002451919,0.000009791659,0.0000334158,0.000003236154,0.000002817406,0.000007090128,0.000002842126,0.993244,0.0007025892,0.005761957,0.000226905,0.000002965417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00931938,0.0003935623,0.9875112,0.0002143732,0.00004404397,0.0000143002,0.00001498108,0.00005576495,0.002432502],"genre_scores_gemma":[0.7113137,0.0009129506,0.2711998,0.0001944976,0.0001625788,0.0001291479,0.00007277854,0.0001164291,0.01589824],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00206945,"threshold_uncertainty_score":0.00692296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0202960388392295,"score_gpt":0.3211433099005387,"score_spread":0.3008472710613092,"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."}}