{"id":"W4240324159","doi":"10.1145/860722.860789","title":"A self organizing social insect model for dynamic frequency allocation in cellular telephone networks","year":2003,"lang":"en","type":"article","venue":"Proceedings of the second international joint conference on Autonomous agents and multiagent systems - AAMAS '03","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Swarm intelligence; Computer science; Swarm behaviour; Cellular network; Telephone network; Distributed computing; Task (project management); Multi-agent system; Division (mathematics); Mobile telephone; Computer network; Particle swarm optimization; Artificial intelligence; Engineering; Machine learning","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007980661,0.0003171638,0.0003665309,0.0002564147,0.0002043701,0.0003312267,0.0009060336,0.0001289485,0.0000449511],"category_scores_gemma":[0.00005601291,0.0002743007,0.0001298859,0.0002433426,0.00004884693,0.0004463391,0.000246235,0.0002269745,0.000007019854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005398807,"about_ca_system_score_gemma":0.0001456415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005111238,"about_ca_topic_score_gemma":0.00003527295,"domain_scores_codex":[0.9976751,0.00004358512,0.0007877556,0.0006738888,0.0004224421,0.0003972426],"domain_scores_gemma":[0.9986005,0.00003664395,0.0006736505,0.0002108214,0.0003908055,0.0000876253],"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":[0.00006098462,0.001009341,0.002337818,0.001134279,0.0006248677,0.000007461792,0.009233588,0.03453232,0.03384659,0.9100708,0.00244978,0.004692125],"study_design_scores_gemma":[0.001052568,0.00007088714,0.001184587,0.0001792578,0.00001941932,0.000005215717,0.0002147329,0.9929415,0.001626949,0.001273661,0.00114522,0.0002860164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7383866,0.0002645655,0.244133,0.001156609,0.00260747,0.004395233,0.00004201324,0.0002083871,0.008806081],"genre_scores_gemma":[0.9936329,0.00006221626,0.004455504,0.0003109924,0.000061959,0.0002843507,0.00001031826,0.00002973618,0.001151989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9584092,"threshold_uncertainty_score":0.9999709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0321991461433465,"score_gpt":0.2381336638841345,"score_spread":0.205934517740788,"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."}}