{"id":"W2526418622","doi":"10.1371/journal.pone.0162624","title":"Towards a DNA Barcode Reference Database for Spiders and Harvestmen of Germany","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Spider Taxonomy and Behavior Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":142,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Bayerisches Staatsministerium für Bildung und Kultus, Wissenschaft und Kunst; Government of Canada; Genome Canada; Ontario Genomics; Bundesministerium für Bildung und Forschung; Ontario Genomics Institute","keywords":"DNA barcoding; Intraspecific competition; Opiliones; Biology; Fauna; Barcode; Spider; Interspecific competition; Zoology; Ecology; Evolutionary biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002816949,0.0009188189,0.001129263,0.01175432,0.000537543,0.00168887,0.001953469,0.001298725,0.009095101],"category_scores_gemma":[0.007467175,0.0006000132,0.0005955677,0.006724218,0.0004106168,0.001792183,0.001889615,0.0009372209,0.01350748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001156084,"about_ca_system_score_gemma":0.002355215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007631658,"about_ca_topic_score_gemma":0.004790023,"domain_scores_codex":[0.9982501,0.0002579454,0.0004194064,0.0005012132,0.0003992596,0.0001720865],"domain_scores_gemma":[0.9958739,0.0006898594,0.001097476,0.0009368639,0.001061818,0.0003401596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001000515,0.0002873861,0.03732998,0.004157207,0.0002158488,0.00120704,0.001577512,0.005269123,0.06547303,0.01422019,0.09091721,0.778345],"study_design_scores_gemma":[0.0001829762,0.0005149168,0.1717646,0.002052399,0.0004347966,0.00264535,0.0008285198,0.01395348,0.04308086,0.007390819,0.7568701,0.000281056],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1496152,0.008522539,0.3129425,0.001419749,0.0007750841,0.001197372,0.4835682,0.02263311,0.01932622],"genre_scores_gemma":[0.0890352,0.002862098,0.2884603,0.0004139867,0.0001483036,0.001377796,0.6075044,0.001387372,0.008810546],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01175432,"threshold_uncertainty_score":0.03042614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08801078880644686,"score_gpt":0.2724569882673507,"score_spread":0.1844461994609038,"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."}}