{"id":"W2897059744","doi":"10.1016/j.tree.2018.09.003","title":"Environmental DNA Time Series in Ecology","year":2018,"lang":"en","type":"review","venue":"Trends in Ecology & Evolution","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":237,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Biodiversity; Environmental DNA; Ecology; Context (archaeology); Temporal scales; Ecosystem; Scale (ratio); Environmental resource management; Geography; Environmental change; Data science; Biology; Climate change; Computer science; Environmental science; Cartography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001380418,0.0008149811,0.001141505,0.003796392,0.0002245786,0.001515305,0.0007644475,0.001550947,0.005283278],"category_scores_gemma":[0.005968377,0.0002807453,0.0004429032,0.006404222,0.001139138,0.002896767,0.001172104,0.001543902,0.000986098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008037672,"about_ca_system_score_gemma":0.002355893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002046237,"about_ca_topic_score_gemma":0.002699237,"domain_scores_codex":[0.9995787,0.00009842757,0.00006362135,0.0001021369,0.0001311788,0.00002590071],"domain_scores_gemma":[0.9962405,0.002870328,0.00037931,0.00009069037,0.0003139541,0.0001052051],"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":[0.00003586036,0.00002472357,0.0008575952,0.01595626,0.0001859242,0.00008678875,0.0001339244,0.0005019105,0.0002100473,0.01301365,0.02425783,0.9447355],"study_design_scores_gemma":[0.00001216098,0.00003653314,0.003422414,0.01308491,0.0003451226,0.0005288063,0.000176006,0.0002535555,0.0001839112,0.02004426,0.9618743,0.00003800879],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001277406,0.9974484,0.0003427202,0.0007315,0.0005286867,0.000002445477,0.00004325272,0.000005238515,0.0007699465],"genre_scores_gemma":[0.001835953,0.9957937,0.000348169,0.000421204,0.001040439,0.000006406358,0.00005040193,0.000003075672,0.0005007018],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005283278,"threshold_uncertainty_score":0.01767427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0164831096116084,"score_gpt":0.2494333643569539,"score_spread":0.2329502547453455,"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."}}