{"id":"W2170078287","doi":"10.1109/ismvl.2012.65","title":"Issues in Multi-valued Multi-modal Sensor Fusion","year":2012,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Redundancy (engineering); Computer science; Modal; Energy consumption; Backup; Overhead (engineering); Fault tolerance; Distributed computing; Sensor fusion; Sensitivity (control systems); Wireless sensor network; Scheme (mathematics); Real-time computing; Embedded system; Engineering; Computer network; Electronic engineering; Artificial intelligence; Electrical engineering; Materials science","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":[0.000430079,0.0002071648,0.0002175521,0.000177373,0.00008764302,0.00007831606,0.0006404403,0.0001386728,0.00004708344],"category_scores_gemma":[0.00004841978,0.000177075,0.00006675994,0.0005082761,0.00004415828,0.0005486604,0.0003787299,0.000201763,0.000275993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006513963,"about_ca_system_score_gemma":0.00001509482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003445048,"about_ca_topic_score_gemma":0.0001258823,"domain_scores_codex":[0.9981149,0.0001528928,0.0002961697,0.0004039532,0.0003133468,0.0007187353],"domain_scores_gemma":[0.9989983,0.00005910405,0.00006692362,0.0006370466,0.0000537655,0.0001848339],"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":[0.00006511364,0.007470195,0.2484221,0.00007491717,0.00007070964,0.0001891378,0.0174007,0.3608757,0.04942168,0.2580822,0.003607565,0.05432004],"study_design_scores_gemma":[0.0007948533,0.00002037121,0.02922987,0.00002116249,0.000001871882,0.00001021596,0.00007678571,0.9610868,0.006643158,0.00000649123,0.001827934,0.0002805488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.308977,0.0004857761,0.687484,0.0003510801,0.0009334169,0.0001747367,5.024149e-7,0.0004056035,0.001187934],"genre_scores_gemma":[0.5896711,0.0000310511,0.407748,0.0002341327,0.00009413901,0.000006619042,0.000001732256,0.0000131894,0.002200082],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.600211,"threshold_uncertainty_score":0.7220908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03569398437709672,"score_gpt":0.2938856426627592,"score_spread":0.2581916582856625,"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."}}