{"id":"W7140457960","doi":"10.1109/ieeeconf67917.2025.11443666","title":"Time-Varying Optimization for Streaming Data Via Temporal Weighting","year":2025,"lang":"","type":"article","venue":"","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Engineering Link (Canada)","funders":"","keywords":"Weighting; Minification; Noise (video); Pattern recognition (psychology)","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":[0.003255426,0.0009842073,0.0009377737,0.0005631141,0.0003522579,0.001237929,0.001566968,0.001195799,0.001334928],"category_scores_gemma":[0.01098851,0.000534643,0.0006951328,0.0009574097,0.001067084,0.002892217,0.001417583,0.002008935,0.0002333838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001301844,"about_ca_system_score_gemma":0.001111003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003992225,"about_ca_topic_score_gemma":0.003422569,"domain_scores_codex":[0.999234,0.000242024,0.00005067387,0.000221407,0.0001854275,0.00006649555],"domain_scores_gemma":[0.9963179,0.002585491,0.0004039846,0.0002337372,0.0003243022,0.0001346699],"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":[0.00004552962,0.00003066138,0.0006843262,0.0000827634,0.00003308275,0.00005597468,0.00005633526,0.938687,0.001385181,0.03468716,0.0006925183,0.02355949],"study_design_scores_gemma":[0.00000187663,0.000007468019,0.0000392484,0.000002666906,0.000002245968,0.000004648178,0.00000313487,0.9937174,0.0001578197,0.005925829,0.0001357142,0.000001923357],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008954865,0.0002170828,0.9900112,0.0001811903,0.00002406893,0.00001974459,0.00004140525,0.00008258774,0.0004679088],"genre_scores_gemma":[0.6604557,0.001020979,0.3332039,0.0002553341,0.0001641191,0.0002458033,0.0003317369,0.0001926553,0.004129708],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003992225,"threshold_uncertainty_score":0.01721656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03591355094568108,"score_gpt":0.3086083266395101,"score_spread":0.2726947756938291,"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."}}