{"id":"W1575579476","doi":"10.1007/978-3-540-28634-9_20","title":"Efficient Data Collection Trees in Sensor Networks with Redundancy Removal","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Redundancy (engineering); Wireless sensor network; Data collection; Computer network; Operating system; Mathematics","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":[0.001284152,0.0006888335,0.001282396,0.0009687767,0.0007046215,0.0008880397,0.001711535,0.0007202822,0.001194325],"category_scores_gemma":[0.003978706,0.0007731465,0.0006138854,0.002635883,0.000630005,0.002550612,0.001336317,0.001226899,0.0004653262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005046314,"about_ca_system_score_gemma":0.0007937457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005809399,"about_ca_topic_score_gemma":0.001053026,"domain_scores_codex":[0.9991042,0.0002329478,0.00007632598,0.0001276967,0.0003716939,0.00008706747],"domain_scores_gemma":[0.9974591,0.001414419,0.0001995025,0.0005311485,0.0003297866,0.00006611904],"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":[0.0004888041,0.0002351775,0.001124721,0.0008870103,0.0001289231,0.0001945766,0.0004550447,0.3115457,0.03825445,0.07584212,0.01166081,0.5591827],"study_design_scores_gemma":[0.00005602184,0.0002229121,0.0005560918,0.00006435603,0.00007983615,0.0004051527,0.00009457712,0.8983912,0.01899419,0.07237194,0.008730991,0.00003282174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01682713,0.001446042,0.9792422,0.000230126,0.00006730553,0.00007776575,0.0001383613,0.0006008128,0.001370284],"genre_scores_gemma":[0.2114721,0.001901574,0.7814269,0.0001458536,0.0001421574,0.0002711877,0.0005227664,0.0002593958,0.003857917],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001711535,"threshold_uncertainty_score":0.006791353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01640715904841092,"score_gpt":0.2294371444101757,"score_spread":0.2130299853617648,"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."}}