{"id":"W4417438735","doi":"10.1109/access.2025.3645218","title":"Toward Safer Mines: A Robust Wireless Sensor Network Placement for Real-World Underground Conditions","year":2025,"lang":"","type":"article","venue":"IEEE Access","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Agencia Nacional de Investigación y Desarrollo","keywords":"Wireless sensor network; Backup; Robustness (evolution); Redundancy (engineering); SAFER; Key distribution in wireless sensor networks; Software deployment; Key (lock)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.000954093,0.001227097,0.001404134,0.0008609849,0.001697344,0.002923248,0.004539929,0.0005631992,0.0001644389],"category_scores_gemma":[0.00006813503,0.001340507,0.0006458965,0.005180354,0.0005642707,0.001538601,0.001213385,0.0006710471,0.00004648346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009700629,"about_ca_system_score_gemma":0.0009582895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006813923,"about_ca_topic_score_gemma":0.004130013,"domain_scores_codex":[0.9913722,0.000512919,0.001959099,0.00257612,0.001000387,0.002579283],"domain_scores_gemma":[0.9926358,0.002566532,0.0008772218,0.002438801,0.0009785523,0.000503076],"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":[0.0002160214,0.0005189772,0.0009342176,0.000387434,0.0004903416,0.00005797939,0.000247626,0.7941149,0.00009589527,0.07622302,0.1244306,0.002283012],"study_design_scores_gemma":[0.003360805,0.0002090999,0.001140617,0.001856249,0.0004799772,0.00001319848,0.0001833926,0.9616005,0.001421951,0.003027353,0.02502791,0.001678945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02957201,0.0006622269,0.9271338,0.005695578,0.01976765,0.002656256,0.0001290601,0.0005204367,0.01386299],"genre_scores_gemma":[0.9487644,0.0009431613,0.01045627,0.003697165,0.003434773,0.0008146612,0.0001562758,0.0001538344,0.03157942],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9191924,"threshold_uncertainty_score":0.9996023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05894208343642082,"score_gpt":0.3260153061928097,"score_spread":0.2670732227563888,"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."}}