{"id":"W2001622031","doi":"10.1016/j.adhoc.2009.08.007","title":"Placement of multiple mobile data collectors in wireless sensor networks","year":2009,"lang":"en","type":"article","venue":"Ad Hoc Networks","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; King Saud University","keywords":"Wireless sensor network; Computer science; Energy consumption; Relay; Sink (geography); Computer network; Solver; Real-time computing; Distributed computing; Engineering; Electrical engineering; Geography","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":[0.00224337,0.001197878,0.001815031,0.001275833,0.001990517,0.001465065,0.002246873,0.001792833,0.0007556591],"category_scores_gemma":[0.005525742,0.00166204,0.0006119696,0.001827483,0.001209313,0.002232792,0.002179408,0.0007807676,0.0004585915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009195392,"about_ca_system_score_gemma":0.0009033994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001306156,"about_ca_topic_score_gemma":0.002083026,"domain_scores_codex":[0.9984663,0.0006596277,0.0001040514,0.0003406805,0.0003138804,0.0001156195],"domain_scores_gemma":[0.9978601,0.0009041268,0.0004021203,0.0003000389,0.0003421021,0.0001915452],"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":[0.0006294079,0.0001588167,0.002806186,0.0002505295,0.0001296121,0.0005614269,0.0002964967,0.8468305,0.02129839,0.01498751,0.001285391,0.1107657],"study_design_scores_gemma":[0.0000452661,0.0003092258,0.0004226383,0.00002029253,0.00004825195,0.0001754424,0.0001525435,0.9816917,0.008102803,0.006909596,0.002096933,0.00002538936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04330926,0.001279551,0.9533432,0.0002797537,0.0001989336,0.0001172692,0.00002428852,0.0002307135,0.001216887],"genre_scores_gemma":[0.6544618,0.00115329,0.3395499,0.00008599792,0.0002005753,0.0002374302,0.00007003079,0.00006128762,0.00417974],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002246873,"threshold_uncertainty_score":0.01186424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01686273908227835,"score_gpt":0.2450416453912845,"score_spread":0.2281789063090062,"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."}}