{"id":"W4380757949","doi":"10.1016/j.ecoinf.2023.102168","title":"A new modelling framework for predator-prey interactions: A case study of an aphid-ladybeetle system","year":2023,"lang":"en","type":"article","venue":"Ecological Informatics","topic":"Insect-Plant Interactions and Control","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Ministério da Ciência, Tecnologia, Inovações e Comunicações; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Computer science; Ecology; Bayesian probability; Bayes' theorem; Model selection; Machine learning; Artificial intelligence; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001111731,0.0007295989,0.0006863987,0.0007636182,0.0008770056,0.002061108,0.001324378,0.001420061,0.003091884],"category_scores_gemma":[0.001740319,0.0003044414,0.001297758,0.0005776607,0.0008469998,0.001657342,0.001433579,0.001129433,0.0002914456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001069225,"about_ca_system_score_gemma":0.001308514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02479491,"about_ca_topic_score_gemma":0.02940623,"domain_scores_codex":[0.9996393,0.0001781254,0.00002830455,0.0000562082,0.00005386311,0.00004419062],"domain_scores_gemma":[0.999135,0.0005659666,0.00006633519,0.00005611687,0.0001104248,0.00006624409],"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":[0.00004466459,0.0001037945,0.00300691,0.0001167736,0.00009037306,0.0005548383,0.0005599598,0.8910291,0.003394855,0.08757744,0.0008296101,0.01269161],"study_design_scores_gemma":[0.000009000237,0.00002498419,0.0003213853,0.00001499465,0.00002177066,0.00006202044,0.0001191806,0.9830328,0.0001889154,0.01345558,0.002738064,0.00001136253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08479192,0.0004258412,0.8984226,0.001128893,0.00008941452,0.0001760946,0.0004421165,0.0003717049,0.01415141],"genre_scores_gemma":[0.6441113,0.0005941494,0.3463294,0.0001457068,0.00006759135,0.0002788141,0.0003208046,0.0001170396,0.008035246],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02479491,"threshold_uncertainty_score":0.04930115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05219698305614867,"score_gpt":0.2861149107466999,"score_spread":0.2339179276905512,"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."}}