{"id":"W2100130157","doi":"10.1109/iecon.2007.4460410","title":"Opportunistic Communication for eNetworks Cyberengineering","year":2007,"lang":"en","type":"article","venue":"","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Wireless sensor network; Context (archaeology); Ubiquitous computing; Interdependence; Architecture; Wireless; Proof of concept; Code (set theory); Distributed computing; Software engineering; Human–computer interaction; Computer network; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007948576,0.0001174888,0.0001345802,0.00006311782,0.0001446387,0.00009389896,0.0006729582,0.00008489095,0.000020149],"category_scores_gemma":[0.00000706175,0.0001118967,0.0000587154,0.0001747923,0.00002724107,0.000191637,0.0001434939,0.000107335,0.00001088998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002787766,"about_ca_system_score_gemma":0.0000407999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008591242,"about_ca_topic_score_gemma":0.00001640534,"domain_scores_codex":[0.9990008,0.00001202821,0.0002866313,0.0002139358,0.0001299834,0.0003566379],"domain_scores_gemma":[0.9985821,0.0004322072,0.00006789924,0.0006638981,0.00008551086,0.0001684482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007439655,0.00002920476,0.00007889097,0.000008339499,0.00001409007,0.000008351146,0.00007968926,0.0002688117,0.00003705676,0.5546431,0.005133483,0.4396915],"study_design_scores_gemma":[0.0002336741,0.00003570615,0.0001555059,0.00001794993,0.000007045443,0.00001666283,0.00002007769,0.9675725,0.00003820713,0.006319609,0.02539879,0.0001842737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000168505,0.0001472596,0.9636592,0.0002666887,0.0003206985,0.0001769011,0.000001358986,0.0002731289,0.0349863],"genre_scores_gemma":[0.773466,0.00003501807,0.2247718,0.0003934548,0.0001050806,0.00001188713,0.00002331928,0.000009899998,0.001183611],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9673037,"threshold_uncertainty_score":0.4563016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01997443963029337,"score_gpt":0.2550144520488549,"score_spread":0.2350400124185615,"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."}}