{"id":"W2022388941","doi":"10.1109/qbsc.2012.6221358","title":"Self-organizing sensor networks: Coverage problem","year":2012,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University","funders":"","keywords":"Wireless sensor network; Computer science; Key distribution in wireless sensor networks; Point (geometry); Planar; Range (aeronautics); Mobile wireless sensor network; Field (mathematics); Real-time computing; Distributed computing; Computer network; Wireless network; Telecommunications; Wireless; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003897061,0.000219703,0.0001908706,0.00007793152,0.0001861248,0.0001944616,0.0007235287,0.0001218825,0.00004601944],"category_scores_gemma":[0.00001189122,0.0001931686,0.00006953105,0.0006885217,0.00002182566,0.0007890416,0.0003868846,0.0002180214,0.000233477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007946706,"about_ca_system_score_gemma":0.00002266316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000010379,"about_ca_topic_score_gemma":0.000002826815,"domain_scores_codex":[0.998045,0.0001036648,0.0002678374,0.0003699535,0.0003142996,0.0008992857],"domain_scores_gemma":[0.9987268,0.0001581424,0.00009643865,0.000682119,0.00007231779,0.0002641863],"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":[0.000005596558,0.0006499898,0.01585907,0.00003886747,0.0001020626,0.0000331248,0.001786625,0.5381338,0.0005662753,0.4174179,0.008829291,0.01657733],"study_design_scores_gemma":[0.0003960012,0.00004576346,0.001173785,0.00002482535,0.00001347031,0.00009355042,0.00003066118,0.9433947,0.001905692,0.0001006146,0.05220071,0.0006202894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01089866,0.0004096898,0.944131,0.0002916377,0.0009238548,0.0001749794,2.052321e-7,0.001448776,0.04172119],"genre_scores_gemma":[0.7003024,0.00005351425,0.2974557,0.0006972593,0.0004699538,0.000006665103,0.000001845379,0.00002493864,0.0009876911],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6894038,"threshold_uncertainty_score":0.7877189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00817558102188721,"score_gpt":0.2019136330747357,"score_spread":0.1937380520528485,"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."}}