{"id":"W4391307028","doi":"10.1109/icfec57925.2023.00019","title":"PLTO: Path Loss-Aware Task Offloading for Vehicular Cooperative Perception","year":2023,"lang":"en","type":"article","venue":"","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University; Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Packet loss; Heuristic; Task (project management); Network packet; Non-line-of-sight propagation; Computer network; Path loss; Path (computing); Real-time computing; Distributed computing; Artificial intelligence; Wireless; Telecommunications; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004029306,0.001105518,0.0006721404,0.0003629491,0.0005829408,0.0007671114,0.001327493,0.0005471897,0.001550797],"category_scores_gemma":[0.000989108,0.0002295691,0.0004447432,0.0003652603,0.0005115282,0.0008094534,0.001475012,0.0007295923,0.0003569793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000548034,"about_ca_system_score_gemma":0.001154011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004571212,"about_ca_topic_score_gemma":0.00554412,"domain_scores_codex":[0.9995777,0.00007517633,0.00001559859,0.00007807454,0.0001035369,0.0001498416],"domain_scores_gemma":[0.9996394,0.0001133897,0.00004270361,0.00007338361,0.00006707983,0.0000640432],"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":[0.0002380401,0.0001961363,0.001132597,0.0001604386,0.00004434707,0.0002272035,0.0002113718,0.8394292,0.030618,0.007241015,0.00453448,0.1159673],"study_design_scores_gemma":[0.00001431762,0.0001051421,0.0002597943,0.000006920327,0.000008696474,0.00005236154,0.0000786357,0.9923304,0.002862466,0.002679206,0.001591155,0.00001099115],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0845988,0.0004256614,0.9047467,0.0002018725,0.0001329909,0.0001725602,0.0001015882,0.001499433,0.008120277],"genre_scores_gemma":[0.9212297,0.0001448598,0.07553653,0.00009913066,0.0000251048,0.0001206719,0.0001778784,0.0001157265,0.00255049],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004571212,"threshold_uncertainty_score":0.009089172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01079816973847163,"score_gpt":0.2297752047674966,"score_spread":0.218977035029025,"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."}}