{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000212427,0.0003952264,0.0004531984,0.0001426487,0.0001435539,0.00005145432,0.000599566,0.0001846667,0.001294995],"category_scores_gemma":[0.00004389902,0.0004022423,0.0002524887,0.0003009982,0.0006944657,0.000275931,0.000643358,0.0002467863,0.0006276123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004015716,"about_ca_system_score_gemma":0.00001343659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00213188,"about_ca_topic_score_gemma":0.0003551643,"domain_scores_codex":[0.9972417,0.0001326663,0.0005538419,0.0008835329,0.0008096626,0.0003785348],"domain_scores_gemma":[0.9987484,0.0002394026,0.0001861902,0.0006439556,0.00001046497,0.000171548],"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":[0.0000786662,0.0001702609,0.1348,0.00008852673,0.0001072046,0.0000484897,0.000408202,0.000121066,0.8628727,0.00001029942,0.0002420506,0.001052496],"study_design_scores_gemma":[0.0003780124,0.0001273987,0.3662209,0.0002351647,0.0001497666,0.000008501796,0.0002754701,0.0002653828,0.6309664,0.0001608604,0.000787707,0.0004243553],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913838,0.0003372858,0.003598876,0.0003282037,0.0001261891,0.001037964,0.002901036,0.00005959444,0.000227083],"genre_scores_gemma":[0.9755702,0.00006178048,0.02320452,0.0003147661,0.0000244672,0.00008651106,0.0005732332,0.00004238202,0.0001221249],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2319063,"threshold_uncertainty_score":0.9998429,"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."}}