{"id":"W3205148898","doi":"10.1371/journal.pone.0257862","title":"Metagenomic analysis provides functional insights into seasonal change of a non-cyanobacterial prokaryotic community in temperate coastal waters","year":2021,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Core Research for Evolutional Science and Technology; Institute of Genetics; Japan Fisheries Research and Education Agency","keywords":"Metagenomics; Biology; Phytoplankton; Bloom; Ecology; Trophic level; Bay; Abundance (ecology); Ecological succession; Temperate climate; Gene; Nutrient; Oceanography; Genetics","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":[0.0002310383,0.0004524417,0.0004503557,0.001410964,0.0003639278,0.0004153714,0.0001422592,0.0002924382,0.0002484302],"category_scores_gemma":[0.0002401625,0.0002177416,0.0004581843,0.00110749,0.000191384,0.0005241508,0.0003320413,0.0002196106,0.00007186965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002236898,"about_ca_system_score_gemma":0.0002618491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002080551,"about_ca_topic_score_gemma":0.00513124,"domain_scores_codex":[0.9998492,0.00001975251,0.00001236353,0.00006038559,0.00002916244,0.00002905329],"domain_scores_gemma":[0.9998667,0.00002262962,0.00004229347,0.00001149435,0.00002728186,0.00002952157],"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":[0.0002660382,0.00005373533,0.2115312,0.000185308,0.0001969061,0.0001584272,0.000300558,0.0006628357,0.7755605,0.00007315179,0.0000666446,0.01094475],"study_design_scores_gemma":[0.000003025704,0.00007746716,0.9828236,0.00001016317,0.00008723299,0.000128764,0.0002907805,0.002140291,0.01387127,0.0001086892,0.0004449271,0.00001362268],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970107,0.0008978864,0.001205981,0.0000326492,0.000005343704,0.000007618599,0.0006408108,0.00001051163,0.0001885207],"genre_scores_gemma":[0.9958339,0.0006754603,0.002267575,0.00003174654,0.0000103257,0.00001575979,0.0009825311,0.00000695128,0.000175746],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002080551,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04857983588126541,"score_gpt":0.2177060231155505,"score_spread":0.1691261872342851,"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."}}