{"id":"W2119416794","doi":"10.1002/jwmg.184","title":"Estimating mountain goat abundance using DNA from fecal pellets","year":2011,"lang":"en","type":"article","venue":"Journal of Wildlife Management","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Forests","funders":"","keywords":"Ungulate; Wildlife; Population; Biology; Abundance (ecology); Genotyping; Feces; Microsatellite; Population size; Ecology; Zoology; Habitat; Demography; Genotype","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000552742,0.0001866366,0.0001693637,0.001041709,0.0003726409,0.0003757888,0.00023838,0.0001502477,0.0008619805],"category_scores_gemma":[0.001138252,0.0001609055,0.00009292343,0.0004117664,0.0003146509,0.0001795383,0.0002077735,0.0001543955,0.0001750292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003467581,"about_ca_system_score_gemma":0.0003022458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03674356,"about_ca_topic_score_gemma":0.1152988,"domain_scores_codex":[0.999723,0.00007937277,0.00001832297,0.00007810197,0.00006930679,0.00003183249],"domain_scores_gemma":[0.999252,0.0001552956,0.0003549971,0.00003924218,0.0001479968,0.00005053753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000568387,0.00001992494,0.9750548,0.00002682262,0.00003401294,0.00005811123,0.0004204372,0.0001512812,0.01542602,0.00002085854,0.000104952,0.008625985],"study_design_scores_gemma":[0.000002816903,0.0000636056,0.9976133,0.000009286968,0.00001296192,0.0001496321,0.000182832,0.0003234622,0.001451056,0.0000149435,0.0001725891,0.000003570263],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982999,0.00008798544,0.00107007,0.000008011161,0.000001397532,0.0000216315,0.0001532942,0.000009136253,0.0003485793],"genre_scores_gemma":[0.9952124,0.0001039216,0.004042459,0.0000147389,0.000003504457,0.00003454259,0.0002475391,0.000002468359,0.0003383433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03674356,"threshold_uncertainty_score":0.07305938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02687521787094889,"score_gpt":0.2471772779825151,"score_spread":0.2203020601115662,"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."}}