{"id":"W2132543522","doi":"10.1111/j.1365-294x.2012.05538.x","title":"Next‐generation sequencing technologies for environmental DNA research","year":2012,"lang":"en","type":"review","venue":"Molecular Ecology","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":940,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Government of Canada; Ontario Genomics Institute; Genome Canada","keywords":"DNA sequencing; Biology; Environmental DNA; Pace; Emerging technologies; Computational biology; Data science; Ecology; Computer science; DNA; Genetics; Biodiversity; Artificial intelligence","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":[0.001668638,0.001236165,0.001658292,0.002937241,0.0004500933,0.001275751,0.001442025,0.00171153,0.006619649],"category_scores_gemma":[0.001297481,0.0003137352,0.0006639475,0.003681593,0.000646332,0.002017419,0.0009814252,0.002281808,0.00631757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000873233,"about_ca_system_score_gemma":0.001791492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00123629,"about_ca_topic_score_gemma":0.00140501,"domain_scores_codex":[0.9992074,0.0001545281,0.00006876252,0.0001213391,0.0003993716,0.00004855858],"domain_scores_gemma":[0.9992923,0.0003163329,0.00007959228,0.0000354454,0.0002215496,0.00005475173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002466121,0.00004476719,0.0001692791,0.01036481,0.00006876872,0.0001898058,0.00006558048,0.0006194066,0.009317799,0.007194941,0.02767662,0.9442636],"study_design_scores_gemma":[0.000004584676,0.00002392774,0.0003709807,0.001254559,0.00003712927,0.0004887733,0.00003697225,0.000173749,0.002329181,0.003770527,0.9914899,0.00001961489],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002900298,0.9865248,0.005880499,0.0008799551,0.0009024951,0.00003987547,0.0001193126,0.00007729177,0.005285731],"genre_scores_gemma":[0.001425814,0.9883395,0.006261641,0.0004063626,0.0004135172,0.00004592874,0.0002221809,0.00001277491,0.002872254],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006619649,"threshold_uncertainty_score":0.02214497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1770530798871936,"score_gpt":0.3292947065633509,"score_spread":0.1522416266761573,"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."}}