{"id":"W3111891248","doi":"10.1002/edn3.174","title":"Comparing CRISPR‐Cas and qPCR eDNA assays for the detection of Atlantic salmon (<i>Salmo salar</i> L.)","year":2020,"lang":"en","type":"article","venue":"Environmental DNA","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts; University of New Brunswick; Université Laval","funders":"Ministère des Forêts, de la Faune et des Parcs","keywords":"Salmo; CRISPR; Biology; Computational biology; Environmental DNA; Fish <Actinopterygii>; Fishery; Gene; Genetics; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001700284,0.000253539,0.000269026,0.00001655715,0.0004161217,0.00002218442,0.0002951879,0.00007706707,0.0002795977],"category_scores_gemma":[0.00002801732,0.0002132107,0.0001161494,0.00008574956,0.0007304277,0.000172742,0.0007119244,0.0001608088,0.0002437132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001872038,"about_ca_system_score_gemma":8.524136e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001738662,"about_ca_topic_score_gemma":0.00002947758,"domain_scores_codex":[0.998492,0.00004923325,0.0002789648,0.0004827873,0.0003804927,0.0003164984],"domain_scores_gemma":[0.9993075,0.0001687779,0.0001529609,0.000236344,7.610134e-7,0.0001336867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007719592,0.00007896168,0.7027131,0.00002356218,0.00005260317,0.000002737193,0.0008325909,0.0002196128,0.2926274,0.000006857309,0.0006346586,0.002730775],"study_design_scores_gemma":[0.0007029386,0.0002730137,0.9014385,0.000008388855,0.0001249583,0.000008609019,0.001006861,0.001935533,0.08362907,0.00003139403,0.01057423,0.0002665035],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953638,0.0004809967,0.001923774,0.0007328503,0.0001109598,0.0006927722,0.00005005041,0.00003987519,0.0006049358],"genre_scores_gemma":[0.9981539,0.0003869217,0.000850051,0.0004226596,0.0000555323,0.00003043979,0.00001375192,0.00002488675,0.00006182508],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2089983,"threshold_uncertainty_score":0.8694479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02010587619325833,"score_gpt":0.2049487843469652,"score_spread":0.1848429081537069,"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."}}