{"id":"W3171192899","doi":"10.1038/s41598-021-91615-3","title":"Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Core Research for Evolutional Science and Technology; Institute of Genetics; King Abdullah University of Science and Technology","keywords":"Metagenomics; Shotgun sequencing; Amplicon; Microbiome; Biology; Amplicon sequencing; Environmental DNA; Shotgun; Computational biology; Database; Genome; 16S ribosomal RNA; Bioinformatics; Ecology; Computer science; Biodiversity; Polymerase chain reaction; Genetics; Gene","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":[0.002036556,0.001316344,0.001303028,0.007547634,0.0008383192,0.001361493,0.001670244,0.0007641394,0.001221875],"category_scores_gemma":[0.003035623,0.000891864,0.0009457276,0.007665341,0.0002238219,0.002153741,0.001609705,0.001016728,0.001255452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008505033,"about_ca_system_score_gemma":0.00253306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01180338,"about_ca_topic_score_gemma":0.01079123,"domain_scores_codex":[0.9988556,0.00008753614,0.0003015224,0.0004001729,0.0002591995,0.00009597639],"domain_scores_gemma":[0.9981902,0.0001565366,0.0003931739,0.000333172,0.0006771379,0.000249761],"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":[0.002049556,0.0009223978,0.2553328,0.004264537,0.0009439932,0.002769879,0.002402447,0.01343106,0.2276191,0.00300376,0.07307088,0.4141896],"study_design_scores_gemma":[0.0005350136,0.0008648548,0.4759107,0.00057768,0.001220325,0.002198662,0.002036436,0.09412535,0.1377522,0.00394317,0.2802056,0.000629867],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3390229,0.002044897,0.1191246,0.0003891081,0.0002034114,0.001145897,0.5112953,0.02155481,0.005219151],"genre_scores_gemma":[0.113142,0.0009399936,0.2245379,0.0001222112,0.00004652442,0.00147619,0.6579306,0.0007755769,0.001029113],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01180338,"threshold_uncertainty_score":0.02346939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02703541114753024,"score_gpt":0.2410599998976032,"score_spread":0.214024588750073,"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."}}