{"id":"W2168724353","doi":"10.1109/aina.2008.77","title":"PACONET: imProved  Ant Colony Optimization Routing Algorithm for Mobile Ad Hoc NETworks","year":2008,"lang":"en","type":"article","venue":"","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Destination-Sequenced Distance Vector routing; Computer network; Ad hoc On-Demand Distance Vector Routing; Ant colony optimization algorithms; Wireless Routing Protocol; Optimized Link State Routing Protocol; Dynamic Source Routing; Distance-vector routing protocol; Link-state routing protocol; Distributed computing; Mobile ad hoc network; Routing protocol; Wireless ad hoc network; Routing (electronic design automation); Algorithm; Wireless; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007342098,0.0005201265,0.0005761616,0.0001421342,0.0007359271,0.0003009568,0.001343077,0.0003860584,0.0001572466],"category_scores_gemma":[0.00006794666,0.0004980587,0.0002689953,0.0008902705,0.0001406325,0.0008892992,0.0005782947,0.0004152167,0.00006682234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000212507,"about_ca_system_score_gemma":0.0001988124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004814628,"about_ca_topic_score_gemma":0.0001402213,"domain_scores_codex":[0.9960753,0.0001343869,0.000843904,0.001248779,0.0004360239,0.001261559],"domain_scores_gemma":[0.9969393,0.0005116495,0.0003968565,0.001405902,0.0003899527,0.0003563376],"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":[0.00003317733,0.000201265,0.00007254368,0.00001401408,0.00007454122,0.000009153158,0.0006344233,0.6361333,0.0001446695,0.0008392083,0.01491472,0.346929],"study_design_scores_gemma":[0.0009696126,0.0002948715,0.00004850471,0.00002830648,0.00002003442,0.0000899361,0.00002483709,0.9082158,0.00007255175,0.0001091333,0.08953738,0.000589065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009914589,0.002175826,0.9914708,0.0001905527,0.00149811,0.002026003,0.00001339273,0.0008087967,0.0008251132],"genre_scores_gemma":[0.01502634,0.00127285,0.9743701,0.00102268,0.0008750047,0.0009775913,0.0001361418,0.00009332081,0.006226034],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3463399,"threshold_uncertainty_score":0.9997471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01881941875000288,"score_gpt":0.2472265425136042,"score_spread":0.2284071237636014,"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."}}