{"id":"W4410315829","doi":"10.1038/s41597-025-05133-2","title":"A beneficial arthropod dataset for agricultural landscapes in Western Canada, and adjacent mountain ecosystems","year":2025,"lang":"en","type":"article","venue":"Scientific Data","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Ducks Unlimited Canada; Calgary Laboratory Services; Simon Fraser University; University of Calgary","funders":"Alberta Innovates; Alberta Innovates Bio Solutions; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Alberta Canola Producers Commission; TD Friends of the Environment Foundation; Institute for Wetland and Waterfowl Research, Ducks Unlimited Canada; Alberta Biodiversity Monitoring Institute; Saskatchewan Canola Development Commission; Alberta Conservation Association","keywords":"Arthropod; Agriculture; Ecosystem; Geography; Ecology; Ecosystem services; Agroforestry; Environmental resource management; Biology; Environmental science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004699743,0.00007564161,0.0001061262,0.00003126215,0.0003007819,0.00007681827,0.0003762688,0.00002667596,0.00004432919],"category_scores_gemma":[0.00005948769,0.00006035557,0.000006085842,0.0001830118,0.0001068762,0.0002022517,0.0006548209,0.00004607151,0.00001275187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009499063,"about_ca_system_score_gemma":0.00005030752,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07734619,"about_ca_topic_score_gemma":0.9964613,"domain_scores_codex":[0.9990551,0.00002676703,0.0001604983,0.0004528943,0.0001108075,0.0001939459],"domain_scores_gemma":[0.9994927,0.00006652635,0.00004059761,0.0003627541,0.000006902043,0.00003053343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001641594,0.00007064349,0.5263965,0.00005008436,0.00002181679,0.000003545835,0.0002002381,0.0006063515,0.0001776909,0.0005290325,0.4705395,0.001388131],"study_design_scores_gemma":[0.0006393375,0.00001612327,0.6315808,0.00003108431,0.0000222649,0.000002810928,0.0007066661,0.01761411,0.00002914422,0.0003215431,0.348855,0.0001810432],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.964861,0.000158983,0.0001384562,0.001335,0.0009522411,0.0003822468,0.03193786,0.000007561535,0.0002266637],"genre_scores_gemma":[0.9771473,0.00001080536,0.0001634053,0.0001347149,0.00001544965,0.00002774225,0.02107864,0.000002392181,0.001419529],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9191151,"threshold_uncertainty_score":0.9287978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01240030823445312,"score_gpt":0.2504399126110274,"score_spread":0.2380396043765743,"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."}}