{"id":"W7028984503","doi":"","title":"Improved clustering techniques in wireless sensor networks","year":2012,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Comics and Graphic Narratives","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cluster analysis; Wireless sensor network; Energy consumption; Latency (audio); Key distribution in wireless sensor networks; Efficient energy use; Fault detection and isolation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007089982,0.0007975615,0.0008599525,0.0006323344,0.001094349,0.0002584054,0.0005238703,0.0006494242,0.0006721144],"category_scores_gemma":[0.00007052771,0.0008037681,0.0003624223,0.00019195,0.0001194681,0.0007269866,0.0001377345,0.001833215,0.00003165708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002922349,"about_ca_system_score_gemma":0.00002622154,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001301548,"about_ca_topic_score_gemma":0.06154766,"domain_scores_codex":[0.9968311,0.0002261803,0.0009423451,0.0007846102,0.0003396225,0.0008761244],"domain_scores_gemma":[0.9982138,0.000166648,0.0005528097,0.0005722072,0.0002790935,0.0002154309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000607097,0.0005440519,0.0001051699,0.0007212613,0.0003748041,0.00006794121,0.001003471,0.00001722468,0.02848331,0.6061645,0.00002015274,0.361891],"study_design_scores_gemma":[0.004443676,0.001079345,0.003283201,0.005767193,0.0008617746,0.00005990905,0.02259522,0.003435267,0.05983112,0.04798753,0.8394217,0.01123404],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8285248,0.000460019,6.445615e-7,0.00001707965,0.002707117,0.0009832926,0.0004623145,0.0003771614,0.1664676],"genre_scores_gemma":[0.9815599,0.0003334467,0.0001315758,0.0001412257,0.0004178539,0.0002507805,0.0006550752,0.0002171903,0.01629293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8394015,"threshold_uncertainty_score":0.9994413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01881621619329478,"score_gpt":0.2313981827797578,"score_spread":0.212581966586463,"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."}}