{"id":"W3135043840","doi":"10.3897/aca.4.e65075","title":"Targeted Next Generation Sequencing improves detection and quantification of rare species from eDNA","year":2021,"lang":"en","type":"article","venue":"ARPHA Conference Abstracts","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Environmental DNA; Abundance (ecology); Biology; Endangered species; Carcinus maenas; Relative species abundance; Ecology; Biodiversity; Habitat; Crustacean; Decapoda","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.00007810927,0.0001148443,0.0001270838,0.00001790035,0.0001574565,0.00005251926,0.00008298209,0.00006543859,0.0006856762],"category_scores_gemma":[0.0000610215,0.0001214902,0.00002720989,0.00008217594,0.0002174215,0.0004580918,0.0001336787,0.00008173769,0.0001059071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001157291,"about_ca_system_score_gemma":0.000009024958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001230171,"about_ca_topic_score_gemma":0.0009294587,"domain_scores_codex":[0.999088,0.00003508455,0.0002078681,0.0003299039,0.000205429,0.0001337356],"domain_scores_gemma":[0.9995554,0.00004648697,0.0001470548,0.0001829061,0.00001872536,0.00004944087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000004767604,0.00002249345,0.01408448,0.000005117329,0.00001341754,0.000004577525,0.0007871329,0.0002320619,0.9769592,0.00001292532,0.00005024096,0.00782364],"study_design_scores_gemma":[0.00007839037,0.0000158434,0.4876512,0.000006458555,0.00001250419,0.0000013648,0.001288679,0.0002826761,0.5103386,0.0001279779,0.0001210903,0.00007518315],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997597,0.0001455555,0.0005573258,0.0001046772,0.0001270119,0.0001025129,0.00003107564,0.00001994715,0.001314834],"genre_scores_gemma":[0.9966142,0.0003173597,0.002717125,0.00005115262,0.00003083103,0.000004078315,0.00006541303,0.000005053021,0.0001948253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4735667,"threshold_uncertainty_score":0.7507674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07022848482725202,"score_gpt":0.2205371167149594,"score_spread":0.1503086318877074,"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."}}