{"id":"W6949514704","doi":"10.5281/zenodo.15684684","title":"CanPests V1","year":2025,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Cerebrovascular and Carotid Artery Diseases","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Genome Canada","keywords":"Barcode; DNA barcoding; Identifier; Host (biology); Distribution (mathematics)","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":[0.0007124599,0.002284447,0.001364361,0.004476484,0.001378646,0.00191532,0.002745159,0.002231567,0.08197358],"category_scores_gemma":[0.006113946,0.0006525459,0.001578086,0.008315421,0.0005158008,0.0008797253,0.001406597,0.001378154,0.05554803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003568598,"about_ca_system_score_gemma":0.008100034,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4709027,"about_ca_topic_score_gemma":0.6147664,"domain_scores_codex":[0.9992416,0.00008523245,0.00006620107,0.0002086172,0.0002258949,0.000172443],"domain_scores_gemma":[0.9981709,0.000429891,0.0001265351,0.00031459,0.0006823611,0.0002757925],"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":[0.00006805498,0.0000163704,0.0008051181,0.0005915559,0.00004544291,0.0000249023,0.00002521606,0.0005798055,0.0001204164,0.0004413952,0.9951094,0.002172307],"study_design_scores_gemma":[0.0002545274,0.00001711554,0.005079203,0.0003653702,0.00007691748,0.0000570235,0.0000918761,0.001080946,0.0002480792,0.001393129,0.9912883,0.00004748588],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001101746,0.00005520165,0.00002962573,0.00003059838,0.000009882755,0.000008819386,0.9991003,0.000183674,0.0004716668],"genre_scores_gemma":[0.0003392441,0.00005707973,0.000206158,0.00003514126,0.000002693286,0.00003740236,0.9988528,0.00004462551,0.00042484],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5290973,"threshold_uncertainty_score":0.9363234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01846934312303889,"score_gpt":0.2574777360187309,"score_spread":0.239008392895692,"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."}}