{"id":"W2127699634","doi":"10.1016/j.ecoinf.2007.02.001","title":"Multi-objective optimization of an ecological assembly model","year":2007,"lang":"en","type":"article","venue":"Ecological Informatics","topic":"Insect and Arachnid Ecology and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Université de Montréal","funders":"Ministry of Economic Affairs","keywords":"Sorting; Mathematical optimization; Evolutionary algorithm; Computer science; Constraint (computer-aided design); Process (computing); Pareto principle; Productivity; Multi-objective optimization; Community structure; Pareto optimal; Ecology; Mathematics; Biology; Algorithm; Economics","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":[0.002664785,0.001509387,0.002213405,0.001920115,0.0009880837,0.001852364,0.002042993,0.00320224,0.004564205],"category_scores_gemma":[0.005716798,0.001537793,0.001589752,0.001310592,0.001364647,0.001612866,0.00207106,0.001436864,0.0004698112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002573763,"about_ca_system_score_gemma":0.001868419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01655519,"about_ca_topic_score_gemma":0.01010265,"domain_scores_codex":[0.9991667,0.0004609363,0.00003514302,0.000148724,0.00009786455,0.00009054168],"domain_scores_gemma":[0.9965277,0.002520784,0.0003677737,0.0001011831,0.0002618704,0.000220644],"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":[0.000009481184,0.000008275719,0.0001097839,0.0000114002,0.00001237662,0.00001372649,0.000007770012,0.9978393,0.00005384484,0.001095165,0.00006918971,0.0007696623],"study_design_scores_gemma":[0.000004306703,0.000005276899,0.00002976898,0.000001849263,0.000003946197,0.000002490532,0.000002601185,0.9993148,0.00001858863,0.0005701897,0.00004464432,0.000001531812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1355287,0.0005838142,0.8510572,0.00102502,0.0001003396,0.0001675795,0.0004944396,0.0004126315,0.01063019],"genre_scores_gemma":[0.7845857,0.0003603412,0.2033085,0.0002396782,0.00008494961,0.0007291111,0.0005938226,0.0002997527,0.009798121],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01655519,"threshold_uncertainty_score":0.03291768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02137592065903715,"score_gpt":0.2878472192778933,"score_spread":0.2664712986188561,"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."}}