{"id":"W6949791533","doi":"10.5281/zenodo.16280992","title":"CanPests V1","year":2025,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"German Colonialism and Identity Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Genome Canada","keywords":"Barcode; DNA barcoding; Identifier; Host (biology); Identification (biology)","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":[0.0008055557,0.00201967,0.001282347,0.004438133,0.001401791,0.002065522,0.002736216,0.001833795,0.1013007],"category_scores_gemma":[0.006007512,0.0006722327,0.001358809,0.009086509,0.0004773071,0.001003371,0.001560173,0.001345432,0.06589044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003640472,"about_ca_system_score_gemma":0.008440932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.443231,"about_ca_topic_score_gemma":0.5818676,"domain_scores_codex":[0.999204,0.0000886829,0.00007226127,0.0002238391,0.0002279383,0.0001832334],"domain_scores_gemma":[0.9980058,0.000408543,0.0001367667,0.0003666328,0.0008036468,0.0002785069],"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":[0.00005130538,0.00001316532,0.0006938239,0.0004749093,0.00003311005,0.00001840874,0.00002710199,0.0003744487,0.0001058437,0.0004823704,0.9959648,0.001760739],"study_design_scores_gemma":[0.0001845659,0.0000118758,0.004324201,0.000314094,0.00005469416,0.00003762471,0.00009858696,0.0006181154,0.0002136563,0.001222223,0.9928792,0.00004107842],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008288528,0.00002975476,0.00002348268,0.00002239439,0.000007288435,0.000009075571,0.9992623,0.0001329256,0.0004298787],"genre_scores_gemma":[0.0002628981,0.00003922915,0.0001991299,0.00002716831,0.000002334879,0.00005000578,0.9989001,0.00005097023,0.0004681356],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.443231,"threshold_uncertainty_score":0.8813022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03778607012456968,"score_gpt":0.2468659623795292,"score_spread":0.2090798922549595,"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."}}