{"id":"W3048861244","doi":"10.1371/journal.pone.0236077","title":"Metabarcoding of native and invasive species in stomach contents of Great Lakes fishes","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"U.S. Geological Survey; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Ontario Trillium Foundation","keywords":"Biology; Predation; Sculpin; Introduced species; Ecology; Invasive species; Zoology; Fishery","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0002995572,0.0002142164,0.0001458687,0.001557417,0.0003009478,0.0003307797,0.0001979593,0.0002318457,0.0007162791],"category_scores_gemma":[0.0005627617,0.0001822326,0.0001910981,0.0008377703,0.0001898564,0.0001955453,0.0003448032,0.0001510249,0.0001981067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002561033,"about_ca_system_score_gemma":0.000261075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008517184,"about_ca_topic_score_gemma":0.02734383,"domain_scores_codex":[0.999761,0.00002966435,0.00002391257,0.0001045499,0.00005834501,0.00002243826],"domain_scores_gemma":[0.9995081,0.00007223283,0.0002335347,0.0000239145,0.0001205094,0.00004174595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001976334,0.00002305342,0.6712651,0.0001626763,0.00005487746,0.0001267596,0.001360816,0.0001915645,0.3015861,0.00009494181,0.0002577072,0.02467882],"study_design_scores_gemma":[0.000003044447,0.00005803756,0.990164,0.00001154359,0.00002702526,0.0001550366,0.0003125332,0.0004211279,0.007950529,0.00001549389,0.0008757875,0.000005797302],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969375,0.0002092036,0.001061147,0.00002828303,0.00000300731,0.00002889928,0.001046408,0.00002912719,0.0006563173],"genre_scores_gemma":[0.9823959,0.0002335056,0.01279978,0.00006546988,0.000006159667,0.00008518971,0.00270908,0.00001421136,0.001690659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008517184,"threshold_uncertainty_score":0.01693523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08498279249131599,"score_gpt":0.201689991184464,"score_spread":0.116707198693148,"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."}}