{"id":"W4312363658","doi":"10.1007/978-3-031-20071-7_34","title":"DVS-Voltmeter: Stochastic Process-Based Event Simulator for Dynamic Vision Sensors","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Voltmeter; Computer science; Noise (video); Event (particle physics); Process (computing); Simulation; Real-time computing; Artificial intelligence; Voltage; Electrical engineering; Physics; Engineering; Image (mathematics)","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":[0.0003267048,0.0005430223,0.0005583714,0.0002817272,0.0001863284,0.0006159809,0.001516759,0.0008671928,0.009575955],"category_scores_gemma":[0.001646185,0.000341639,0.0004090893,0.0003031265,0.0002544229,0.000573574,0.0005339623,0.001065638,0.001646399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004924151,"about_ca_system_score_gemma":0.0006016808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001955633,"about_ca_topic_score_gemma":0.001935754,"domain_scores_codex":[0.9998121,0.00003783294,0.00001130377,0.00003249029,0.00008997368,0.00001628081],"domain_scores_gemma":[0.9996603,0.0001805323,0.00002380534,0.00004361897,0.00006744057,0.00002428771],"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":[0.0002684763,0.00009615783,0.001024166,0.0002191289,0.00007321312,0.0001309447,0.00007596814,0.8819633,0.01694072,0.02153864,0.01536207,0.06230716],"study_design_scores_gemma":[0.0000115765,0.000008415902,0.00003822588,0.00000245023,0.000002487506,0.00001218949,0.000001544946,0.9950534,0.001873901,0.001276468,0.001715941,0.000003516852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009640187,0.0001088492,0.9746236,0.0001225674,0.0001008985,0.00007388843,0.001033387,0.01056822,0.003728406],"genre_scores_gemma":[0.642018,0.0003307248,0.3397999,0.0003291578,0.00007901686,0.0004826776,0.002531856,0.002664634,0.01176397],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009575955,"threshold_uncertainty_score":0.03203481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01101852337293851,"score_gpt":0.2745387723037066,"score_spread":0.2635202489307681,"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."}}