{"id":"W6920795804","doi":"10.6084/m9.figshare.26589972.v1","title":"Additional file 1 of Hidden diversity: DNA metabarcoding reveals hyper-diverse benthic invertebrate communities","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Agriculture and Agri-Food Canada","funders":"","keywords":"Invertebrate; Benthic zone; DNA sequencing; DNA barcoding; DNA; Biodiversity","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002122412,0.00154243,0.001387505,0.003498616,0.001480067,0.00206802,0.002452408,0.001422296,0.8448828],"category_scores_gemma":[0.02370101,0.0008566558,0.00109497,0.005077541,0.0005009503,0.002113843,0.00175743,0.001313172,0.2609773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009609071,"about_ca_system_score_gemma":0.002102247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006027623,"about_ca_topic_score_gemma":0.009542209,"domain_scores_codex":[0.9988563,0.0001750828,0.0001647077,0.0003569587,0.0002901601,0.0001568274],"domain_scores_gemma":[0.9827611,0.01204775,0.0009347538,0.001310083,0.002412003,0.0005343528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002954908,0.00009453735,0.0020771,0.002843838,0.00004836524,0.0000854143,0.0001161343,0.0003772275,0.0006581386,0.0006842685,0.9837421,0.008977409],"study_design_scores_gemma":[0.002460592,0.0002650005,0.02287096,0.002423902,0.0002017277,0.0005860875,0.0005026551,0.001725828,0.003774034,0.009941838,0.9550325,0.0002149415],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001704817,0.00001291507,0.0006333023,0.00006605531,0.00003113161,0.00006383936,0.997593,0.0007356104,0.0006936931],"genre_scores_gemma":[0.003847858,0.00008163242,0.007071971,0.0004031869,0.00008109724,0.001195406,0.9796117,0.002107296,0.005599797],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8448828,"threshold_uncertainty_score":0.2212559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05682050377111429,"score_gpt":0.220344813486883,"score_spread":0.1635243097157686,"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."}}