{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005102154,0.0007618712,0.0005064973,0.0006451359,0.0006266927,0.0009527539,0.0006955197,0.0005399596,0.0201711],"category_scores_gemma":[0.0005734095,0.0001699994,0.0001783629,0.0005988885,0.0004147275,0.001057006,0.0009314953,0.0007352711,0.006600272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003375042,"about_ca_system_score_gemma":0.0007435579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001720536,"about_ca_topic_score_gemma":0.001818597,"domain_scores_codex":[0.999543,0.00008627978,0.00003010744,0.0001239082,0.0001718487,0.00004495142],"domain_scores_gemma":[0.9996946,0.00004473699,0.00003291057,0.0001227048,0.0000725205,0.00003254338],"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":[0.002150093,0.0004331983,0.006503118,0.0005555479,0.0001521608,0.001687677,0.0007640024,0.008568445,0.3302482,0.0382353,0.1090431,0.5016592],"study_design_scores_gemma":[0.0006018911,0.001552898,0.00870457,0.0001297121,0.0001597765,0.00173521,0.0002084487,0.09686237,0.1507598,0.004432979,0.7346815,0.0001708107],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1308206,0.001975639,0.4999818,0.001307755,0.0007263388,0.002229063,0.004946716,0.08721083,0.2708013],"genre_scores_gemma":[0.728259,0.001307335,0.116245,0.0005850662,0.0002057596,0.001103868,0.00716443,0.001278503,0.1438511],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0201711,"threshold_uncertainty_score":0.06747907,"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."}}