{"id":"W4403406654","doi":"10.1128/msystems.00317-24","title":"Marine biofilms: cyanobacteria factories for the global oceans","year":2024,"lang":"en","type":"article","venue":"mSystems","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Japan Science and Technology Agency; Ministry of Education, Culture, Sports, Science and Technology; Japan Society for the Promotion of Science; Hong Kong University of Science and Technology; Research Grants Council, University Grants Committee; Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","keywords":"Cyanobacteria; Metagenomics; Ecology; Marine habitats; Biology; Seawater; Water column; Ecological niche; Geomicrobiology; Biofilm; Oceanography; Habitat; Microbial ecology; Geology; Paleontology; Environmental biotechnology; Bacteria","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001458852,0.00008280845,0.00009500864,0.00000522725,0.0002055305,0.00004414112,0.0002709111,0.00006860153,0.003415573],"category_scores_gemma":[0.00001560192,0.00005253726,0.00005416277,0.0001070141,0.0001396898,0.00005202148,0.0001998388,0.00008122027,0.0006370197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009182058,"about_ca_system_score_gemma":0.000008844789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008992883,"about_ca_topic_score_gemma":0.003507389,"domain_scores_codex":[0.9994773,0.00007144974,0.0001087784,0.0001325563,0.00003787168,0.0001720861],"domain_scores_gemma":[0.9995482,0.0001874182,0.00001902367,0.0002172108,0.000002903802,0.00002525816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003333064,0.0001866822,0.2722407,0.0004352966,0.0004590595,0.0000197988,0.003730907,0.0003412891,0.164499,0.03828532,0.5009333,0.01853537],"study_design_scores_gemma":[0.00007334004,0.000088716,0.03314785,0.000008165745,0.00001639025,0.00001598059,0.0001112283,0.0003333396,0.0002544702,0.001252174,0.9646071,0.00009119622],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9753718,0.0002564028,0.0005529501,0.001150889,0.003672893,0.0005671819,0.0002905097,0.0001493848,0.01798804],"genre_scores_gemma":[0.9983657,0.00001660782,0.00005430921,0.000156656,0.0001271353,0.00002671706,0.00004974064,0.000005980431,0.001197136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4636739,"threshold_uncertainty_score":0.9974954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0127335031238998,"score_gpt":0.2481041683394925,"score_spread":0.2353706652155927,"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."}}