{"id":"W4407398811","doi":"10.32942/x2nw5c","title":"Designing epigenetic clocks for wildlife research","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Environment and Climate Change Canada; Churchill Northern Studies Centre; Parks Canada; World Wildlife Fund","keywords":"Wildlife; Workflow; Epigenetics; Sampling (signal processing); Pace; Computer science; Environmental resource management; Geography; Biology; Ecology; Environmental science; Telecommunications; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02361542,0.0007080093,0.0008516837,0.001986114,0.001476153,0.003546906,0.00230367,0.001277859,0.004546113],"category_scores_gemma":[0.05827003,0.001002931,0.001372093,0.002269092,0.001830237,0.003554306,0.004121958,0.001644252,0.002237349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002367478,"about_ca_system_score_gemma":0.006819968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01303999,"about_ca_topic_score_gemma":0.02179467,"domain_scores_codex":[0.9924912,0.004082733,0.0004898662,0.001734805,0.000882104,0.0003193088],"domain_scores_gemma":[0.9818323,0.008127434,0.00155313,0.004733898,0.002941732,0.0008114617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00115865,0.0001510159,0.1314335,0.002327527,0.000584149,0.0004580729,0.005644351,0.135241,0.05255377,0.1446575,0.02233983,0.5034506],"study_design_scores_gemma":[0.0003972784,0.000457068,0.04306794,0.0009787248,0.0004138321,0.0004175932,0.00256959,0.2024252,0.09176424,0.3670315,0.2899102,0.0005668894],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03018738,0.000937729,0.9519237,0.001669024,0.0003530543,0.0005149007,0.004255524,0.005588364,0.004570307],"genre_scores_gemma":[0.1045306,0.0007419919,0.8874822,0.0005545875,0.00007520162,0.0009029348,0.003057011,0.001037242,0.001618296],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02361542,"threshold_uncertainty_score":0.1248918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08943904364619491,"score_gpt":0.4059680479188199,"score_spread":0.316529004272625,"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."}}