{"id":"W1968833385","doi":"10.1145/2529975","title":"The GINSENG system for wireless monitoring and control","year":2013,"lang":"en","type":"article","venue":"ACM Transactions on Sensor Networks","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"Petro-Canada","funders":"Seventh Framework Programme","keywords":"Computer science; Software deployment; Wireless sensor network; Automation; Oil refinery; Wireless; Debugging; Industrial control system; Embedded system; Control (management); Computer network; Telecommunications; Engineering; Software engineering; Operating system","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":[0.0003043048,0.000281955,0.0002708852,0.00008120287,0.001244784,0.0005664627,0.0009261515,0.0001799938,0.0000017536],"category_scores_gemma":[0.00001808851,0.000214283,0.000138647,0.0003342103,0.0001103625,0.0002924932,0.00001875998,0.0003812105,0.00001626723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008412005,"about_ca_system_score_gemma":0.00001632882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004733283,"about_ca_topic_score_gemma":0.000007335199,"domain_scores_codex":[0.9979977,0.0001474947,0.0003700737,0.0005398206,0.0002656505,0.0006792881],"domain_scores_gemma":[0.9959188,0.002394612,0.000126705,0.001188551,0.0001858146,0.0001855514],"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":[0.00003186736,0.00004049956,0.00008793013,0.0000184294,0.0000961518,0.00000411689,0.0001023704,0.7829844,0.0004202406,0.002439377,0.0001066646,0.213668],"study_design_scores_gemma":[0.0008817996,0.00009466937,0.0004205914,0.00009758449,0.00003120561,0.00003651597,0.0002718056,0.9955941,0.001239125,0.00006722987,0.000975155,0.0002901767],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02806046,0.0003734231,0.9667184,0.001442957,0.00211626,0.0007422823,0.000002834529,0.0004522025,0.00009115641],"genre_scores_gemma":[0.9815533,0.0001953146,0.01714336,0.00009137651,0.0003549772,0.0003357468,7.539364e-7,0.00004023119,0.0002849437],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9534928,"threshold_uncertainty_score":0.9573996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01044459524527198,"score_gpt":0.2141432253968032,"score_spread":0.2036986301515313,"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."}}