{"id":"W2003314357","doi":"10.1145/1143549.1143823","title":"Integrating wireless EEGs into medical sensor networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Wireless sensor network; Computer science; Key distribution in wireless sensor networks; Wireless; Mobile wireless sensor network; Real-time computing; Wireless network; Computer network; Telecommunications","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":[0.0005271693,0.0002749,0.0002869146,0.0001181618,0.0002369326,0.0002538281,0.001415361,0.0002789055,0.0001023403],"category_scores_gemma":[0.00005417613,0.000224789,0.0001155769,0.0007868281,0.0001314679,0.0002830488,0.0004687513,0.0004793755,0.00006732155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007722373,"about_ca_system_score_gemma":0.00007611088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008992744,"about_ca_topic_score_gemma":0.0007961573,"domain_scores_codex":[0.9972007,0.000148395,0.0005105814,0.0006524253,0.000835328,0.0006526212],"domain_scores_gemma":[0.9984193,0.0003735341,0.0001211725,0.0007320586,0.0001246478,0.0002293154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005607617,0.0001866903,0.00196541,0.00001023406,0.00001958572,0.0002186885,0.0001555586,0.291515,0.0003291423,0.5770846,0.00993137,0.1185781],"study_design_scores_gemma":[0.0002436723,0.00002835014,0.0002705272,0.00005121857,0.000002903651,0.00004747002,0.00002986905,0.99531,0.0006231774,0.0004847413,0.002610941,0.0002971138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03813703,0.0001426307,0.9353979,0.001562366,0.0008087137,0.00008969323,1.17671e-7,0.0007995602,0.02306203],"genre_scores_gemma":[0.8570684,0.00001611523,0.1398361,0.0009658677,0.0006625929,0.00001082053,0.000007468581,0.00002537795,0.001407286],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8189313,"threshold_uncertainty_score":0.916663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004325107697092241,"score_gpt":0.2122732825897573,"score_spread":0.207948174892665,"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."}}