{"id":"W2013376029","doi":"10.1002/nem.793","title":"A random obstacle‐based mobility model for delay‐tolerant networking","year":2011,"lang":"en","type":"article","venue":"International Journal of Network Management","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Key Laboratory of Computer Network and Information Integration","keywords":"Obstacle; Computer science; Node (physics); Mobility model; Path (computing); Computer network; Delay-tolerant networking; Signal strength; Distributed computing; Real-time computing; Routing (electronic design automation); Routing protocol; Wireless sensor network; Optimized Link State Routing Protocol","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":[0.0004322063,0.0005732898,0.0005145258,0.0006640396,0.0004626708,0.0007080444,0.001237716,0.0006759479,0.001049035],"category_scores_gemma":[0.001320345,0.0002599338,0.0005574076,0.0004682419,0.0005254048,0.0009929792,0.0007834514,0.0005366862,0.0001956432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008429254,"about_ca_system_score_gemma":0.0006499119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005150648,"about_ca_topic_score_gemma":0.002956008,"domain_scores_codex":[0.9996376,0.0001100333,0.00002021636,0.0000539233,0.000121756,0.00005636012],"domain_scores_gemma":[0.9995263,0.0001767971,0.0001062004,0.00004474883,0.0001026171,0.00004349682],"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":[0.00001826343,0.00001533614,0.0003102064,0.00001940296,0.00001071025,0.00009793556,0.00003001426,0.9725038,0.001058543,0.02281271,0.000405627,0.002717366],"study_design_scores_gemma":[0.000003837139,0.0000129795,0.000049414,0.000003165007,0.000004538366,0.00002457666,0.00000624114,0.9963359,0.0001452326,0.002670031,0.0007384982,0.000005675323],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06484942,0.000560938,0.9231259,0.000470903,0.0002209182,0.0001004709,0.000195998,0.0002830508,0.01019233],"genre_scores_gemma":[0.9322124,0.0008750248,0.05795209,0.0001430754,0.00007970113,0.0002290524,0.0002377878,0.00008171071,0.008189147],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005150648,"threshold_uncertainty_score":0.01024133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06295481932385799,"score_gpt":0.2715307868331963,"score_spread":0.2085759675093383,"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."}}