{"id":"W2021984249","doi":"10.1142/s0129626407003034","title":"COMPARING MINIMUM NEIGHBORHOOD EVALUATION SCHEMES FOR FINDING SPATIALLY ROBUST SOLUTIONS","year":2007,"lang":"en","type":"article","venue":"Parallel Processing Letters","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"National Science Council","keywords":"Robustness (evolution); Fitness function; Mathematical optimization; Neighbourhood (mathematics); Computer science; Algorithm; Mathematics; Genetic algorithm","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":[0.00581945,0.0007614169,0.00125657,0.002661454,0.0004732269,0.001105958,0.001271553,0.001622671,0.001362217],"category_scores_gemma":[0.02343068,0.0003260635,0.001062424,0.001630661,0.0008632701,0.002242066,0.001423997,0.0007159321,0.0002578161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001265264,"about_ca_system_score_gemma":0.000559472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001797221,"about_ca_topic_score_gemma":0.001625225,"domain_scores_codex":[0.99768,0.0008718818,0.0002063986,0.0002029231,0.0009323388,0.0001065043],"domain_scores_gemma":[0.9903342,0.006805597,0.0005390194,0.001020546,0.001150629,0.0001500541],"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":[0.0006523289,0.0001298059,0.002719269,0.0003726691,0.0001923625,0.0000761101,0.000273334,0.7203446,0.006582792,0.03346517,0.001018186,0.2341733],"study_design_scores_gemma":[0.00003959879,0.0003344009,0.001418777,0.00004872811,0.00005496458,0.00009258195,0.00007864292,0.9824809,0.005735902,0.00849478,0.001181061,0.00003960071],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.166894,0.002990282,0.8216618,0.0003240283,0.0001274384,0.0002784458,0.0001188324,0.0004454799,0.00715974],"genre_scores_gemma":[0.6086766,0.0009675291,0.3875316,0.00006218719,0.00004576248,0.0003026898,0.000215294,0.0001500296,0.002048206],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00581945,"threshold_uncertainty_score":0.03077656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08517098334736357,"score_gpt":0.3201502356648206,"score_spread":0.234979252317457,"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."}}