{"id":"W4408806121","doi":"10.1002/oik.11196","title":"Local environment and sampling bias drive parasite prevalence estimates in freshwater fish communities","year":2025,"lang":"en","type":"article","venue":"Oikos","topic":"Parasite Biology and Host Interactions","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières; Université de Montréal","funders":"","keywords":"Parasite hosting; Fish <Actinopterygii>; Sampling (signal processing); Sampling bias; Ecology; Biology; Freshwater fish; Distance sampling; Fishery; Geography; Environmental science; Statistics; Abundance (ecology); Sample size determination; Mathematics; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001067532,0.00009270325,0.00009531558,0.00003683844,0.0001401053,0.00001944809,0.0001228358,0.00006052053,0.001714348],"category_scores_gemma":[0.00001293915,0.00008333357,0.00001823533,0.00004686275,0.0003716488,0.0001188229,0.0001767487,0.0001498123,0.0001906179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008246526,"about_ca_system_score_gemma":0.00000341963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008166903,"about_ca_topic_score_gemma":0.004161419,"domain_scores_codex":[0.9994573,0.00005442613,0.0001252505,0.0001455764,0.00005413989,0.0001632816],"domain_scores_gemma":[0.9995903,0.0001951437,0.00002579347,0.0001580733,0.000001346674,0.00002933081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001417839,0.00004312965,0.9923497,0.00000951051,0.000008047338,0.000002455891,0.0005471866,0.001370161,0.001649256,0.00007381746,0.0002597386,0.003672775],"study_design_scores_gemma":[0.0001489844,0.00002796951,0.9778209,0.0000647473,0.00001210233,0.000005725225,0.000311545,0.002498552,0.002634328,0.0005949479,0.01577424,0.000105946],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931841,0.00007805682,0.001855929,0.0003329215,0.00005446681,0.0001035676,0.00002636807,0.00001726332,0.004347296],"genre_scores_gemma":[0.9964425,0.0002084853,0.00122749,0.0004449071,0.000004266703,0.00003163824,0.00001464661,0.000003444436,0.001622628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0155145,"threshold_uncertainty_score":0.9991982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02845857449435911,"score_gpt":0.3139279582751519,"score_spread":0.2854693837807927,"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."}}