{"id":"W4392924133","doi":"10.1656/045.031.0106","title":"PCR-Based Amplification of a Cox1 Mini-DNA Barcode Gene from Feces: A Non-Invasive Molecular Technique to Identify Environmental DNA Samples of Maritime Shrew (Sorex maritimensis)","year":2024,"lang":"en","type":"article","venue":"Northeastern Naturalist","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University; York University","funders":"","keywords":"Shrew; Feces; Environmental DNA; Biology; Barcode; DNA barcoding; DNA; Sorex; Gene; Zoology; Genetics; Ecology; Biodiversity; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004853878,0.0007346089,0.0003227926,0.0009970659,0.0003011154,0.0003362175,0.0006196913,0.000486077,0.001029453],"category_scores_gemma":[0.001322019,0.0003924819,0.0003661655,0.0004914714,0.0004798636,0.0003141566,0.0003165105,0.0006093744,0.0008852097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004450118,"about_ca_system_score_gemma":0.0009018871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007758168,"about_ca_topic_score_gemma":0.03831693,"domain_scores_codex":[0.999223,0.0001020451,0.00005342765,0.0003138234,0.0002230334,0.00008469649],"domain_scores_gemma":[0.9989073,0.0002313364,0.0004195561,0.00007585686,0.0002822362,0.00008369161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006098397,0.00005158037,0.008002852,0.0001721287,0.00000858326,0.00008034278,0.0001866798,0.0000585176,0.982634,0.00006305119,0.00008767332,0.008593651],"study_design_scores_gemma":[0.00004569142,0.0009802743,0.2118609,0.0001831047,0.0001019724,0.001492888,0.0005498324,0.003057031,0.7724801,0.0001111822,0.009091793,0.00004527468],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.843159,0.001800626,0.1452284,0.0002090439,0.0001055356,0.00163047,0.003657836,0.0005612298,0.003647746],"genre_scores_gemma":[0.6069785,0.00187974,0.3722066,0.0005084514,0.00003839458,0.001373726,0.007478425,0.000168562,0.00936763],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007758168,"threshold_uncertainty_score":0.01542604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01286464631971719,"score_gpt":0.2367696742648483,"score_spread":0.2239050279451311,"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."}}