{"id":"W6899344792","doi":"10.5883/ds-cangibel","title":"Using DNA barcoding to identify Prussian carp (Carassius gibelio, Bloch, 1782) in southern Alberta, Canada","year":2023,"lang":"en","type":"dataset","venue":"Barcode of Life Data Systems","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"DNA barcoding; Barcode; Mitochondrial DNA; Sequence (biology); DNA sequencing; DNA","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008199305,0.0009271053,0.0007165219,0.005485129,0.002146723,0.001515167,0.002112525,0.0007001664,0.007143553],"category_scores_gemma":[0.002135314,0.0005730278,0.0006540919,0.01025394,0.0006799774,0.0004287445,0.001084914,0.0009637896,0.003902672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01526315,"about_ca_system_score_gemma":0.02372068,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9933848,"about_ca_topic_score_gemma":0.9969091,"domain_scores_codex":[0.9991905,0.00003136258,0.00005314905,0.0001697506,0.0003838318,0.000171468],"domain_scores_gemma":[0.9974202,0.0001633694,0.000147556,0.0001807211,0.001861965,0.0002261978],"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":[0.0003925711,0.0001081136,0.1813327,0.002138454,0.0004033667,0.0004677435,0.00099709,0.005609131,0.002168151,0.001931815,0.7440423,0.06040845],"study_design_scores_gemma":[0.0001541967,0.00003109438,0.6095886,0.001022963,0.0002501736,0.0001777959,0.001669372,0.002652973,0.001253562,0.000683683,0.3823867,0.00012889],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02360375,0.0006602939,0.0004671668,0.0001718877,0.00005938823,0.0000640975,0.9695425,0.0002948415,0.005136052],"genre_scores_gemma":[0.03450913,0.0005362278,0.001722971,0.0000839283,0.00001012506,0.00008802467,0.9588344,0.00008212621,0.004133139],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01526315,"threshold_uncertainty_score":0.1107424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09899601282433622,"score_gpt":0.3412950179235631,"score_spread":0.2422990050992269,"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."}}