{"id":"W2148491588","doi":"10.1371/journal.pone.0013991","title":"Environmental Barcoding Reveals Massive Dinoflagellate Diversity in Marine Environments","year":2010,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Protist diversity and phylogeny","field":"Biochemistry, Genetics and Molecular Biology","cited_by":138,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Environment Research Council; Sight Research UK; University at Buffalo; Genome Canada","keywords":"Dinoflagellate; DNA barcoding; Biology; Barcode; Dinophyceae; Ecology; Species diversity; Zoology; Phytoplankton","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003647163,0.0002295671,0.0002520728,0.001867116,0.0006216256,0.0007178464,0.0002726806,0.0003481766,0.0006115285],"category_scores_gemma":[0.001463272,0.0001511987,0.0001781092,0.001938051,0.0004710293,0.0003901794,0.001072498,0.0003697898,0.0001740187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007192434,"about_ca_system_score_gemma":0.000400748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0124438,"about_ca_topic_score_gemma":0.03741274,"domain_scores_codex":[0.9994821,0.00004232702,0.00004023549,0.0002042988,0.0001480039,0.00008310362],"domain_scores_gemma":[0.9986278,0.0002049866,0.0006423054,0.0001025987,0.0003210374,0.0001013766],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001270222,0.00002289247,0.8851193,0.0001277772,0.00006198225,0.0001558142,0.001622075,0.0003104244,0.09403539,0.0001454843,0.0001684473,0.01810344],"study_design_scores_gemma":[0.000001833848,0.00003220654,0.9902715,0.00002162856,0.00003365243,0.0001856513,0.000650416,0.0004985405,0.006925792,0.00008509296,0.001285072,0.000008557658],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981068,0.0001819129,0.0005830392,0.00001843764,0.000002067762,0.000005273225,0.000648475,0.00001276369,0.0004413313],"genre_scores_gemma":[0.9958711,0.0001527456,0.002273218,0.00003753748,0.000003211361,0.000013088,0.001503664,0.000007330836,0.0001380501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0124438,"threshold_uncertainty_score":0.02474278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01911503527290457,"score_gpt":0.1882149410956395,"score_spread":0.1690999058227349,"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."}}