{"id":"W2923941421","doi":"10.1016/j.tree.2019.02.013","title":"Aquatic Landscape Genomics and Environmental Effects on Genetic Variation","year":2019,"lang":"en","type":"review","venue":"Trends in Ecology & Evolution","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":175,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; University of British Columbia","funders":"National Aeronautics and Space Administration; National Science Foundation","keywords":"Genomics; Biology; Genetic diversity; Population genomics; Ecology; Inference; Data science; Population; Genome; Computer science; Artificial intelligence; Genetics","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":[0.0008991901,0.0008293493,0.001356498,0.002407346,0.0001893534,0.00112999,0.000653585,0.001236759,0.005056974],"category_scores_gemma":[0.001894738,0.0002716302,0.0004392343,0.004240979,0.0008496771,0.00119525,0.0009534422,0.001141379,0.0009398109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006360639,"about_ca_system_score_gemma":0.00154459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003331976,"about_ca_topic_score_gemma":0.005905834,"domain_scores_codex":[0.9997777,0.00004187781,0.00002649692,0.00007548941,0.00005910851,0.000019351],"domain_scores_gemma":[0.9988149,0.0008413165,0.0001383523,0.00002700576,0.0001209025,0.00005758226],"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":[0.00005915779,0.00003141232,0.0008723495,0.01194105,0.0002073097,0.00007812001,0.00005579441,0.0002843655,0.0003865641,0.003931704,0.01682667,0.9653255],"study_design_scores_gemma":[0.00002789941,0.00007490611,0.008570471,0.01395623,0.0007670825,0.0006412638,0.0001668053,0.0001578377,0.0003017646,0.009196796,0.9660931,0.00004581719],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001238953,0.9985179,0.0001196262,0.0003448201,0.0001489011,0.000001168647,0.00002578698,0.000004143641,0.0007136731],"genre_scores_gemma":[0.0008647324,0.9980305,0.0001433836,0.0002956685,0.0003221853,0.000002729367,0.0000336811,0.000001570943,0.0003055618],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005056974,"threshold_uncertainty_score":0.01691729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0149456863456391,"score_gpt":0.2357048991668909,"score_spread":0.2207592128212518,"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."}}