{"id":"W3002633637","doi":"10.3390/fi12020019","title":"MCCM: An Approach for Connectivity and Coverage Maximization","year":2020,"lang":"en","type":"article","venue":"Future Internet","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Computer science; Maximization; Distributed computing; Quality of service; Wireless sensor network; Internet of Things; Cover (algebra); Wireless; Object (grammar); Computer network; Real-time computing; Telecommunications; Computer security; Artificial intelligence","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":[0.001215256,0.001271417,0.00117399,0.001855749,0.0008128816,0.001075465,0.002586212,0.001777027,0.002495999],"category_scores_gemma":[0.003469225,0.0004835699,0.001040536,0.002176775,0.0009115556,0.00164268,0.00201313,0.001373098,0.0005265265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001692379,"about_ca_system_score_gemma":0.001382171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003413282,"about_ca_topic_score_gemma":0.003429426,"domain_scores_codex":[0.998973,0.0003346556,0.00003854911,0.0002017628,0.000326394,0.0001256369],"domain_scores_gemma":[0.9988355,0.0006640144,0.0001027574,0.0001092608,0.000221963,0.00006658648],"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":[0.00009556626,0.00009509024,0.001031745,0.0002887481,0.0001169,0.0002235383,0.0001980691,0.7119012,0.00793625,0.1035701,0.01406501,0.1604777],"study_design_scores_gemma":[0.00001520383,0.00004474809,0.0001361145,0.00001460657,0.00001632638,0.0001274637,0.00002408884,0.9769419,0.001172794,0.01608258,0.005414401,0.000009834098],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002787542,0.0004049629,0.9931743,0.0002456761,0.00004590496,0.0000582711,0.00004652738,0.0001912773,0.00304565],"genre_scores_gemma":[0.2812689,0.001090016,0.7088985,0.000544831,0.0003327047,0.0005629976,0.000291474,0.0002950628,0.006715496],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003413282,"threshold_uncertainty_score":0.01227915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01609739819753067,"score_gpt":0.2163228459384299,"score_spread":0.2002254477408993,"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."}}