{"id":"W4282832159","doi":"10.1111/1755-0998.13667","title":"Do pseudogenes pose a problem for metabarcoding marine animal communities?","year":2022,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada; Ontario Genomics; Genome Canada","keywords":"Biology; Pseudogene; Computational biology; Evolutionary biology; Environmental DNA; Ecology; Zoology; Genetics; Genome; Biodiversity; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003428411,0.0001745629,0.0002134696,0.00005583797,0.00120729,0.00002354139,0.0005417725,0.00004510579,0.004424029],"category_scores_gemma":[0.00001389537,0.0001897552,0.0001184285,0.0001367072,0.0004057587,0.00005945356,0.003554747,0.0001767295,0.00008149386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002381254,"about_ca_system_score_gemma":0.000002274951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002294602,"about_ca_topic_score_gemma":0.0001011913,"domain_scores_codex":[0.9986671,0.0002203132,0.0001724806,0.0003022982,0.0002485238,0.0003893414],"domain_scores_gemma":[0.999469,0.0001020778,0.00009920491,0.0002666595,0.000003437596,0.00005964925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001135701,0.0002065545,0.9558594,0.0000125142,0.0001203586,0.00005259808,0.002239754,0.001883721,0.03655542,0.0001252301,0.001941526,0.0008893703],"study_design_scores_gemma":[0.001791307,0.001913228,0.7418835,0.000004015141,0.000233621,0.0001320381,0.01253467,0.0005102911,0.007416897,0.001353526,0.2314159,0.0008110343],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929689,0.0001235657,0.00002432298,0.0006470321,0.00006694661,0.000520742,0.000060625,0.00004917793,0.005538678],"genre_scores_gemma":[0.989329,0.00001816381,0.008860507,0.000920142,0.00001330351,0.0003029547,0.00003031424,0.00002044931,0.0005051837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2294744,"threshold_uncertainty_score":0.9964861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01462743599929782,"score_gpt":0.2151142532359079,"score_spread":0.20048681723661,"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."}}