{"id":"W2098833650","doi":"10.1109/icc.2006.255032","title":"Snapshot Capacity of Multi Hop Ad Hoc Networks","year":2006,"lang":"en","type":"article","venue":"2006 IEEE International Conference on Communications","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Snapshot (computer storage); Computer science; Wireless ad hoc network; Hop (telecommunications); Computer network; Distributed computing; Algorithm; Wireless; 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":[0.000637935,0.0004079301,0.0004462456,0.0007492971,0.0003612645,0.001130159,0.0008945956,0.000372869,0.002387248],"category_scores_gemma":[0.004104874,0.0002006803,0.0002166661,0.0006341194,0.001199168,0.002375765,0.0009807425,0.0006180218,0.0002341061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006239295,"about_ca_system_score_gemma":0.0005121419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000886404,"about_ca_topic_score_gemma":0.0003243947,"domain_scores_codex":[0.9995636,0.0001183186,0.00001546965,0.00006152836,0.0001499001,0.00009115183],"domain_scores_gemma":[0.9976045,0.001605078,0.0001418213,0.000140015,0.0003758792,0.0001326141],"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":[0.000150831,0.00003599935,0.001094234,0.0002564511,0.00005027262,0.0003644447,0.0002952872,0.4964838,0.01139253,0.4499204,0.001841526,0.03811425],"study_design_scores_gemma":[0.000008743894,0.00007891826,0.0004018538,0.0000322278,0.00001163231,0.0001908468,0.0001201084,0.8546025,0.003558467,0.1388647,0.002102899,0.00002714609],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1668476,0.002894937,0.8097965,0.0003480038,0.00008143935,0.00006313235,0.0002181094,0.000390554,0.01935971],"genre_scores_gemma":[0.9834146,0.00136974,0.01268468,0.00005590004,0.00004563812,0.00005269232,0.00009879933,0.00002962256,0.002248348],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002387248,"threshold_uncertainty_score":0.007986188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09865646480188171,"score_gpt":0.3194057243605338,"score_spread":0.220749259558652,"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."}}