{"id":"W4404187547","doi":"10.1139/facets-2023-0051","title":"Spatial and seasonal determinants of arthropod community composition across an agro-ecosystem landscape","year":2024,"lang":"en","type":"article","venue":"FACETS","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Arthropod; Geography; Ecology; Composition (language); Ecosystem; Environmental resource management; Environmental science; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.0002207825,0.00009890739,0.0001783881,0.0007363366,0.0004682408,0.000481006,0.0002185323,0.0001208232,0.0007051341],"category_scores_gemma":[0.0005963242,0.000139577,0.0001068847,0.0007485821,0.0005617244,0.0001803156,0.0002821357,0.0001371027,0.00007800556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001861353,"about_ca_system_score_gemma":0.0007475491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3929592,"about_ca_topic_score_gemma":0.7947909,"domain_scores_codex":[0.9998007,0.00003024452,0.000007915566,0.00006600707,0.00003589899,0.00005929506],"domain_scores_gemma":[0.9994531,0.00006373991,0.0001750739,0.00003108996,0.000140048,0.0001370145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000697951,0.00001666761,0.982982,0.00001594346,0.00003614099,0.00005526668,0.0005378511,0.0001173969,0.01346945,0.000025819,0.00005134814,0.002622429],"study_design_scores_gemma":[4.585832e-7,0.000005032233,0.99978,6.153769e-7,0.000001612547,0.000008195962,0.00008836204,0.00005419693,0.00003396277,0.000003420259,0.00002376851,5.680699e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997112,0.00003779051,0.00004097062,0.000005383265,2.10384e-7,0.000002215499,0.00009389257,0.000001000067,0.0001072312],"genre_scores_gemma":[0.9996152,0.00002532685,0.0001033231,0.000004618762,4.885827e-7,0.000002686954,0.0001310424,8.061746e-7,0.0001164812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3929592,"threshold_uncertainty_score":0.7813439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04455400778690633,"score_gpt":0.266647789237382,"score_spread":0.2220937814504757,"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."}}