{"id":"W2794459133","doi":"10.7287/peerj.preprints.26814v1","title":"Experimental design considerations for assessing marine biodiversity using environmental DNA","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Environmental DNA; Biodiversity; Transect; Environmental resource management; Environmental monitoring; Marine biodiversity; Sampling (signal processing); Replicate; Environmental science; Geography; Ecology; Biology; Computer science; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.06548413,0.002048386,0.001948668,0.001588001,0.003223011,0.002801536,0.003710689,0.002910723,0.009603074],"category_scores_gemma":[0.08816999,0.002153823,0.001937719,0.001591015,0.002948203,0.001778828,0.002488486,0.003311532,0.001824082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001743221,"about_ca_system_score_gemma":0.002628863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002549174,"about_ca_topic_score_gemma":0.006886448,"domain_scores_codex":[0.934867,0.04336555,0.006370266,0.004493971,0.009440406,0.001462814],"domain_scores_gemma":[0.9204034,0.0475653,0.005327409,0.01432482,0.01087721,0.001501839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.02887142,0.008291699,0.04158106,0.01135748,0.002078928,0.002076071,0.003812196,0.01895421,0.6327173,0.04917616,0.01208833,0.1889952],"study_design_scores_gemma":[0.008890917,0.08725838,0.1119935,0.002181225,0.005215457,0.002289449,0.002242594,0.03668519,0.3868163,0.09605758,0.2591961,0.001173328],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1032297,0.001737017,0.8015568,0.00266958,0.003026268,0.0707494,0.003143447,0.001203802,0.01268409],"genre_scores_gemma":[0.07140028,0.0007624405,0.7593664,0.002056486,0.0003092905,0.1605285,0.001167288,0.0004261989,0.003983111],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06548413,"threshold_uncertainty_score":0.3463173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09361753492548812,"score_gpt":0.2753342793103921,"score_spread":0.181716744384904,"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."}}