{"id":"W4415235880","doi":"10.3897/arphapreprints.e175083","title":"CanPests V1.0: A reference dataset for arthropod pests of Canada integrating DNA barcodes","year":2025,"lang":"en","type":"article","venue":"","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Government of Canada; Ontario Genomics; Genome Canada; Gordon and Betty Moore Foundation","keywords":"DNA barcoding; Barcode; PEST analysis; Guild; Checklist; Taxonomy (biology); Species name; Identifier","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009362762,0.001378345,0.001035106,0.01123588,0.002192366,0.001911994,0.002439218,0.0009188403,0.02199301],"category_scores_gemma":[0.007703356,0.0006379532,0.0009328622,0.02012655,0.0005091703,0.0009525924,0.001444853,0.00122287,0.009353363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01638095,"about_ca_system_score_gemma":0.03567661,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9732741,"about_ca_topic_score_gemma":0.9796794,"domain_scores_codex":[0.9987246,0.00007427738,0.0001313625,0.0002306513,0.0005754908,0.0002635105],"domain_scores_gemma":[0.9919866,0.0004833818,0.0005732284,0.0005679826,0.005869316,0.0005195332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001569787,0.00002832685,0.02204883,0.001275001,0.0001355879,0.0001269732,0.000329275,0.001268769,0.0008982954,0.002252646,0.9423924,0.02908694],"study_design_scores_gemma":[0.00005673178,0.00001264549,0.06106371,0.0006511621,0.00009406366,0.0001249602,0.0003343995,0.001208005,0.0007791016,0.0009601646,0.9346127,0.000102343],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001354463,0.0002161768,0.0004813959,0.00005715935,0.00001541889,0.00003496684,0.9944035,0.0005348147,0.002902148],"genre_scores_gemma":[0.004631999,0.0003414779,0.002695647,0.00007186033,0.000005275216,0.00009262421,0.990582,0.0001759592,0.001403117],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02672595,"threshold_uncertainty_score":0.1188527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01357464025111051,"score_gpt":0.2358922072847253,"score_spread":0.2223175670336147,"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."}}