{"id":"W1497740160","doi":"","title":"A complex adaptive system based on squirrels behaviors for distributed resource allocation","year":2006,"lang":"en","type":"article","venue":"Web Intelligence and Agent Systems An International Journal","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Manitoba","funders":"","keywords":"Computer science; Scalability; Distributed computing; Resource allocation; Resource (disambiguation); Class (philosophy); Set (abstract data type); Variety (cybernetics); Architecture; Artificial intelligence; Computer network; Database","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":[0.0005825945,0.000349778,0.0003690204,0.0003230975,0.000727307,0.0008756821,0.0009052278,0.0004820247,0.003005113],"category_scores_gemma":[0.001820129,0.0001508121,0.0003147778,0.0002219869,0.000852554,0.0009890783,0.0007942715,0.000674852,0.0004553923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005990306,"about_ca_system_score_gemma":0.0005518027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001805489,"about_ca_topic_score_gemma":0.002209731,"domain_scores_codex":[0.9997503,0.00005960354,0.00001830608,0.00006540633,0.00007999381,0.00002635711],"domain_scores_gemma":[0.9992664,0.000246392,0.00008331548,0.0001609048,0.000125612,0.000117386],"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":[0.0006250576,0.000360029,0.009230383,0.0003358507,0.0002006912,0.0006303275,0.001337245,0.3383346,0.154502,0.1936434,0.007491002,0.2933095],"study_design_scores_gemma":[0.00006062775,0.0002324483,0.001009317,0.00001549747,0.00003910031,0.0002437787,0.00008549239,0.9560042,0.007152983,0.02256001,0.01256086,0.00003570078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09587729,0.0001589887,0.8939918,0.0002783113,0.00007990597,0.0001417856,0.00002852027,0.001923706,0.007519712],"genre_scores_gemma":[0.7514843,0.0001238754,0.2440949,0.0001203278,0.00004352244,0.0001397296,0.00005918815,0.0001110664,0.003823014],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003005113,"threshold_uncertainty_score":0.0100531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04430210844436849,"score_gpt":0.2888149854682313,"score_spread":0.2445128770238628,"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."}}