{"id":"W2035075941","doi":"10.1109/systems.2010.5482327","title":"Context-aware collective decision making in distributed environments","year":2010,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Context (archaeology); Wireless sensor network; Process (computing); Information fusion; Sensor fusion; Decision process; State (computer science); Decision support system; Information processing; Artificial intelligence; Data mining; Distributed computing; Machine learning; Computer network; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001780746,0.0001357859,0.0001481274,0.0001137393,0.0001008761,0.00009278944,0.0006821289,0.0001180091,0.0000629135],"category_scores_gemma":[0.00005703942,0.000123206,0.00003994734,0.0005282752,0.00005006857,0.0002176398,0.0003084373,0.000302933,0.00005420805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001127816,"about_ca_system_score_gemma":0.00003508972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002049774,"about_ca_topic_score_gemma":0.0005641322,"domain_scores_codex":[0.9987075,0.00004396612,0.0002220602,0.0004287223,0.0002763394,0.0003214184],"domain_scores_gemma":[0.999031,0.0003295924,0.00006433862,0.0004904447,0.00001834935,0.00006624439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001395554,0.001214606,0.07591726,0.000007778698,0.0000534988,0.0004052098,0.002013893,0.2950926,0.009368023,0.1323116,0.006244852,0.4772312],"study_design_scores_gemma":[0.0008489152,0.00004744003,0.06398566,0.00005190333,0.000002077679,0.0000172785,0.00005470654,0.9257592,0.00301401,0.001729601,0.004157902,0.0003313253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2310249,0.0000101741,0.7667614,0.00009595847,0.0004483942,0.0001070466,0.000002144375,0.00007376425,0.001476273],"genre_scores_gemma":[0.9772364,0.000002426729,0.02221324,0.0002050156,0.00002621766,0.00001109994,0.000003709854,0.00000862949,0.0002932409],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7462116,"threshold_uncertainty_score":0.5024193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007525184501188754,"score_gpt":0.229544223181194,"score_spread":0.2220190386800052,"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."}}