{"id":"W2739770983","doi":"10.1109/icc.2017.7996977","title":"An efficient approach for data transmission in power-constrained wireless sensor network","year":2017,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Computer science; Wireless sensor network; Survivability; Task (project management); Transmission (telecommunications); Data transmission; Wireless; Computer network; Real-time computing; Power consumption; Power (physics); Embedded system; Telecommunications; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.001190454,0.000299381,0.0003744018,0.0001011055,0.0006548428,0.0006313878,0.005626571,0.0001946772,0.000008894445],"category_scores_gemma":[0.00002789792,0.0002592001,0.00007835021,0.000223223,0.0001660638,0.0006228682,0.0005365593,0.0002278146,0.000003677859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003950917,"about_ca_system_score_gemma":0.00008954301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007588274,"about_ca_topic_score_gemma":0.00003007336,"domain_scores_codex":[0.9968897,0.0001240424,0.000442611,0.001317987,0.0003765565,0.0008491774],"domain_scores_gemma":[0.9947996,0.000167187,0.0002136637,0.004483607,0.00007983494,0.0002561788],"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":[0.00004561842,0.0004550069,0.0004564294,0.00002017856,0.0000143372,0.00001777048,0.0002243063,0.8917483,0.0005748702,0.0413214,0.0004447304,0.06467707],"study_design_scores_gemma":[0.001000158,0.00009191527,0.0009454325,0.00004337982,0.000006548268,0.00001186925,0.00003884971,0.9959362,0.0003105779,0.0000725,0.001176934,0.0003656217],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03656784,0.00005742261,0.9560791,0.0004584328,0.0003478988,0.0005536196,0.000008644989,0.0002518766,0.005675194],"genre_scores_gemma":[0.6007592,0.00000624758,0.3988344,0.00009806848,0.0001081862,0.00001696177,0.00005011321,0.00002023968,0.0001065077],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5641914,"threshold_uncertainty_score":0.999986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03407893427508332,"score_gpt":0.2859395002954417,"score_spread":0.2518605660203584,"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."}}