{"id":"W2944974408","doi":"10.1007/s10878-019-00413-1","title":"An evolutionary approach for the target search problem in uncertain environment","year":2019,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Defence Research and Development Canada; Université Laval","funders":"","keywords":"Theory of computation; Evolutionary algorithm; Mathematical optimization; Computer science; Mathematical economics; Mathematics; Theoretical computer science; 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":[{"model":"gemma","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001390696,0.0000967261,0.0001773565,0.0001363246,0.00007961986,0.00008431826,0.0007446085,0.00007207509,0.00000696853],"category_scores_gemma":[0.0000352217,0.00007086279,0.00005772512,0.0002404856,0.00002246658,0.0006726916,0.00005618953,0.0002081327,0.00000228283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001921994,"about_ca_system_score_gemma":0.0001744974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005869191,"about_ca_topic_score_gemma":1.036321e-9,"domain_scores_codex":[0.9985864,0.0001787303,0.0003835394,0.000169977,0.000486544,0.000194877],"domain_scores_gemma":[0.9990829,0.0001899559,0.0002473171,0.0002721542,0.000144382,0.00006327804],"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":[0.00004107434,0.0001959228,0.0009186643,0.000009236736,0.0000124831,0.000002047345,0.0003476227,0.992761,0.00003643766,0.005191971,0.0001316907,0.0003518179],"study_design_scores_gemma":[0.001321839,0.0004804847,0.000586214,0.00001556272,0.000005596911,0.00001983193,0.00005828475,0.9945028,0.00003899649,0.002721973,0.000162895,0.00008556736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001692688,0.0001274557,0.9974348,0.0004200518,0.00122776,0.0004882801,0.000001127133,0.00001140848,0.0001198336],"genre_scores_gemma":[0.01957496,0.00002072729,0.9801162,0.00002680526,0.0002062368,0.00001201576,0.000007511167,0.000009267882,0.00002626998],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01940569,"threshold_uncertainty_score":0.2889701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01441698364284747,"score_gpt":0.2473417136439673,"score_spread":0.2329247300011199,"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."}}