{"id":"W4402980888","doi":"10.1109/otcon60325.2024.10687955","title":"Advanced Machine Learning Techniques for Data Prediction in WSNs","year":2024,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Computer science; Machine learning; Artificial intelligence; Wireless sensor network; Computer network","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":[0.001381676,0.001011082,0.0009066525,0.001196475,0.0003335404,0.0007243296,0.001104974,0.0008143123,0.001108921],"category_scores_gemma":[0.004161139,0.0003869942,0.0008108288,0.001807312,0.0004886213,0.001622449,0.0008080975,0.002543512,0.0006450296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000631818,"about_ca_system_score_gemma":0.0006279632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003429963,"about_ca_topic_score_gemma":0.002750055,"domain_scores_codex":[0.9992161,0.0002068949,0.00007169857,0.000180305,0.0002800863,0.00004492104],"domain_scores_gemma":[0.9987592,0.0006537805,0.0001117185,0.0001493326,0.0002995824,0.00002647523],"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":[0.00006003393,0.00008121048,0.001777077,0.0002070867,0.0001350008,0.00009588173,0.0001006433,0.5913292,0.003191134,0.02770639,0.004485355,0.370831],"study_design_scores_gemma":[0.000002191729,0.00001112189,0.0001304497,0.00001035081,0.000005267235,0.00001582396,0.000005220038,0.9877675,0.0006146516,0.0102395,0.001193046,0.000004975782],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002459232,0.001059609,0.9950126,0.0002728122,0.00008891352,0.00001402445,0.00004659484,0.0004366567,0.0006094995],"genre_scores_gemma":[0.3374701,0.005295459,0.6509621,0.0004110159,0.0005841312,0.0002342378,0.0004992695,0.0001726947,0.004371017],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003429963,"threshold_uncertainty_score":0.007307112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02239608890920594,"score_gpt":0.2786557548152187,"score_spread":0.2562596659060128,"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."}}