{"id":"W2108773413","doi":"10.1109/iwqos.2007.376548","title":"Probabilistic Field Coverage using a Hybrid Network of Static and Mobile Sensors","year":2007,"lang":"en","type":"article","venue":"International Workshop on Quality of Service","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Scheduling (production processes); Probabilistic logic; Wireless sensor network; Distributed computing; Overhead (engineering); Real-time computing; Exploit; Computer network; Engineering","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":[0.0009585575,0.0006131104,0.0007445286,0.0007723972,0.000510139,0.0008292221,0.001422083,0.000918429,0.0008643047],"category_scores_gemma":[0.002278032,0.0005834984,0.0005339811,0.0008513364,0.0007593535,0.001776036,0.001357365,0.0005025738,0.0002097915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007255569,"about_ca_system_score_gemma":0.0004567929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001549881,"about_ca_topic_score_gemma":0.001488479,"domain_scores_codex":[0.9990659,0.0002739418,0.00003021998,0.0002451656,0.0002797906,0.0001049479],"domain_scores_gemma":[0.9990589,0.0005087025,0.0001338996,0.0001040215,0.0001268012,0.00006763631],"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":[0.0002778731,0.00008533888,0.001821112,0.00009042968,0.00006010802,0.0002364085,0.0001336356,0.9126811,0.01826722,0.01885139,0.0006055806,0.04688979],"study_design_scores_gemma":[0.00001969689,0.0001096543,0.0002685354,0.000004596029,0.00001652799,0.00008655134,0.00002490172,0.993317,0.001583166,0.003841072,0.0007173604,0.00001086588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05635859,0.0003135813,0.9407073,0.0001815368,0.0000272628,0.00004766003,0.000034824,0.0002295948,0.002099468],"genre_scores_gemma":[0.898309,0.0003678225,0.09836559,0.00008949466,0.00006184517,0.0001330121,0.00005729635,0.00003127007,0.002584579],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001549881,"threshold_uncertainty_score":0.005264282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03383180869374273,"score_gpt":0.3232705276578743,"score_spread":0.2894387189641316,"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."}}