{"id":"W2149628778","doi":"10.1109/icc.2005.1495010","title":"Very low cost sensor localization for hostile environments","year":2005,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wireless sensor network; Software deployment; Computer science; Battlefield; Key distribution in wireless sensor networks; Real-time computing; Wireless; Computer network; Simple (philosophy); Wireless network; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003924462,0.0004656985,0.000441078,0.0005167358,0.0004142358,0.0004691676,0.0008487906,0.0006170084,0.002061488],"category_scores_gemma":[0.00140367,0.0002198739,0.0002653444,0.0005045155,0.0005357665,0.001226706,0.0008825067,0.0005129693,0.001166026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003405209,"about_ca_system_score_gemma":0.000254176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005818642,"about_ca_topic_score_gemma":0.0008274982,"domain_scores_codex":[0.999509,0.0001938201,0.00001353287,0.00005567562,0.0001939591,0.00003395822],"domain_scores_gemma":[0.9994085,0.000214191,0.00009472048,0.0001382953,0.0001137529,0.00003055171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002739159,0.00006727484,0.001726588,0.0006532069,0.00007859078,0.0004803011,0.000238158,0.2107357,0.1133209,0.09184733,0.01727669,0.5633013],"study_design_scores_gemma":[0.0000748095,0.000613065,0.001735358,0.00006877565,0.00008454535,0.001917014,0.0001183898,0.8322413,0.05094738,0.03576935,0.07634524,0.00008474983],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009444605,0.001026712,0.985698,0.0002840292,0.00009632682,0.00002325239,0.00001367824,0.000864759,0.002548717],"genre_scores_gemma":[0.544543,0.001796551,0.4425695,0.0002855854,0.0001562946,0.00009570897,0.000118618,0.0001644364,0.01027036],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002061488,"threshold_uncertainty_score":0.006896377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007073241654648386,"score_gpt":0.2011926278509333,"score_spread":0.1941193861962849,"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."}}