{"id":"W1594101221","doi":"10.1007/978-3-540-77024-4_4","title":"Localized Mobility Control Routing in Robotic Sensor Wireless Networks","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer network; Computer science; Routing (electronic design automation); Wireless sensor network; Geographic routing; Key distribution in wireless sensor networks; Wireless; Transmission (telecommunications); Dynamic Source Routing; Node (physics); Destination-Sequenced Distance Vector routing; Distributed computing; Power control; Path (computing); Routing protocol; Wireless network; Power (physics); Engineering; Telecommunications","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":[0.0003429441,0.0005690202,0.0005875374,0.0004255752,0.0002639815,0.0006665317,0.001139336,0.0006340379,0.001444217],"category_scores_gemma":[0.0007356167,0.000300941,0.0002619694,0.0007535327,0.0006315491,0.001136066,0.0006500184,0.0006760374,0.0005291077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004752555,"about_ca_system_score_gemma":0.0002606488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006924539,"about_ca_topic_score_gemma":0.0006881649,"domain_scores_codex":[0.9998029,0.00005627903,0.000009213632,0.00004363235,0.00007062811,0.00001741271],"domain_scores_gemma":[0.9998141,0.00008914759,0.00002342774,0.00003882555,0.00002552046,0.000008979175],"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":[0.00007672678,0.00007102201,0.0002171638,0.0003692773,0.00004057409,0.0001170046,0.0001380886,0.429059,0.01516657,0.1271586,0.01468861,0.4128974],"study_design_scores_gemma":[0.00002092001,0.000127256,0.0003749853,0.00005870782,0.00002715809,0.0001886388,0.00005385725,0.8564968,0.005188107,0.09767237,0.03976364,0.00002758377],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01212673,0.01353038,0.9605342,0.0006131427,0.0004617797,0.00004832835,0.00004565933,0.0008910958,0.01174864],"genre_scores_gemma":[0.6597079,0.01790421,0.2709951,0.0003021101,0.0009704505,0.0003639348,0.00030406,0.0002965461,0.04915576],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001444217,"threshold_uncertainty_score":0.004831374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01510876504713235,"score_gpt":0.2398289347973364,"score_spread":0.224720169750204,"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."}}