{"id":"W2968115793","doi":"10.3390/microorganisms7080250","title":"Metagenomic Sequencing Identifies Highly Diverse Assemblages of Dinoflagellate Cysts in Sediments from Ships’ Ballast Tanks","year":2019,"lang":"en","type":"article","venue":"Microorganisms","topic":"Marine Ecology and Invasive Species","field":"Environmental Science","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Laboratory for Marine Ecology and Environmental Science; National Natural Science Foundation of China-Shandong Joint Fund; National Oceanic and Atmospheric Administration; Qingdao National Laboratory for Marine Science and Technology; University of Windsor; National Natural Science Foundation of China; Great Lakes Protection Fund; Old Dominion University; U.S. Environmental Protection Agency","keywords":"Dinoflagellate; Ballast; Bay; Biology; Algal bloom; Dinophyceae; Metagenomics; Alexandrium tamarense; Bloom; Environmental DNA; Sediment; Plankton; Ecology; Oceanography; Fishery; Phytoplankton; Biodiversity; Paleontology; Geology","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":[0.0001994305,0.0003318698,0.000222952,0.0008370273,0.0003536373,0.0005567661,0.0001641709,0.0002905237,0.0004655981],"category_scores_gemma":[0.0003086984,0.0002496821,0.0002361739,0.000618574,0.0002067136,0.0002980957,0.0004441593,0.0002105026,0.0001801887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004473293,"about_ca_system_score_gemma":0.0003611942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0107676,"about_ca_topic_score_gemma":0.02741789,"domain_scores_codex":[0.9997533,0.00002388932,0.00002171516,0.00008915781,0.0000610902,0.0000508671],"domain_scores_gemma":[0.9997857,0.00002349326,0.00008170158,0.000012623,0.00005628564,0.00004012408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002516687,0.00004255909,0.3579677,0.00005868043,0.00003992353,0.0002019929,0.001121691,0.0002181043,0.6313494,0.00002022977,0.00009535971,0.008632732],"study_design_scores_gemma":[0.000003010919,0.0001575231,0.9771662,0.000006914466,0.00002700136,0.0002349991,0.0008268883,0.00031277,0.02059704,0.0000115207,0.0006482328,0.0000078051],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992402,0.00009132799,0.0001711842,0.00001477252,0.000001499425,0.000004999455,0.0003070739,0.000005614652,0.0001632527],"genre_scores_gemma":[0.9970294,0.0001428159,0.001057327,0.00003635406,0.000002167109,0.000008755304,0.001182415,0.000004237295,0.0005364927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0107676,"threshold_uncertainty_score":0.02140987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009519149577959901,"score_gpt":0.1967089257485733,"score_spread":0.1871897761706134,"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."}}