{"id":"W4232598951","doi":"10.1145/1454609","title":"Proceedings of the 5th ACM symposium on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks","year":2008,"lang":"en","type":"paratext","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wireless ad hoc network; Computer science; Wireless sensor network; Variety (cybernetics); Pleasure; Ubiquitous computing; Field (mathematics); Vehicular ad hoc network; Wireless; World Wide Web; Telecommunications; Data science; Computer network; Artificial intelligence; Human–computer interaction","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01005939,0.002269021,0.002713438,0.001957154,0.0009582292,0.004800481,0.001846726,0.001757374,0.02571218],"category_scores_gemma":[0.01679146,0.0006839393,0.0009438022,0.001723445,0.001044086,0.003913008,0.002001225,0.003264723,0.008646409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001643994,"about_ca_system_score_gemma":0.002908867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004943626,"about_ca_topic_score_gemma":0.00557272,"domain_scores_codex":[0.9910172,0.003125424,0.0006884272,0.0005827611,0.004173748,0.0004124495],"domain_scores_gemma":[0.983927,0.005475865,0.0006066466,0.00158663,0.0064261,0.00197771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008705319,0.0007986636,0.008633522,0.001020695,0.0004341174,0.000314484,0.0004087458,0.006807926,0.004638104,0.0146044,0.4799645,0.4815044],"study_design_scores_gemma":[0.0002015696,0.00133425,0.01404471,0.001273283,0.0003839065,0.0009666267,0.0005495707,0.05453648,0.005464732,0.01719007,0.903891,0.0001638964],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.05214715,0.1836805,0.4052729,0.02364762,0.07598642,0.003272951,0.007353837,0.006069558,0.242569],"genre_scores_gemma":[0.2555549,0.1312203,0.22904,0.003566913,0.02845051,0.002867175,0.02141415,0.002613557,0.3252724],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9742878,"threshold_uncertainty_score":0.08601588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02250639246681217,"score_gpt":0.2498988918752827,"score_spread":0.2273924994084706,"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."}}