{"id":"W3004484569","doi":"10.3390/toxins11120723","title":"Metabolome Variation between Strains of Microcystis aeruginosa by Untargeted Mass Spectrometry","year":2019,"lang":"en","type":"article","venue":"Toxins","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Environment and Climate Change Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Metabolome; Cyanobacteria; Microcystis aeruginosa; Metabolomics; Microcystin; Mass spectrometry; Microcystis; Chemistry; Biology; Chromatography; Bacteria; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000225276,0.0001285167,0.0002683188,0.00003942525,0.00003358005,0.00001217961,0.0002064245,0.00008784717,0.005338232],"category_scores_gemma":[0.00001161381,0.0001211936,0.00005889193,0.0002684634,0.00003634522,0.0001281391,0.0000514612,0.0001042062,0.0008480837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001145581,"about_ca_system_score_gemma":0.00001078234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005933419,"about_ca_topic_score_gemma":0.00008309,"domain_scores_codex":[0.9989344,0.00004615574,0.0002933266,0.000239297,0.0002572113,0.0002296483],"domain_scores_gemma":[0.9994201,0.00005228538,0.0001780739,0.0002705495,0.000005543382,0.00007344375],"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":[0.000004689608,0.0000429163,0.337023,0.00002852625,0.00004943736,8.991267e-7,0.0002697929,0.0002591106,0.6602944,0.000605474,0.0009358485,0.0004859126],"study_design_scores_gemma":[0.000848289,0.0002282512,0.9433096,0.00002417804,0.00007613708,0.000003960825,0.0001242,0.004371271,0.03993042,0.001079822,0.009551151,0.0004527194],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9783359,0.00003864022,0.0113349,0.00005959785,0.0001269936,0.0002410004,0.0003779666,0.00002752507,0.009457435],"genre_scores_gemma":[0.9938186,0.000006964471,0.004539964,0.00003197361,0.00003666063,0.000002918564,0.00009197202,0.00001355809,0.001457392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.620364,"threshold_uncertainty_score":0.9999298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004654605138595341,"score_gpt":0.1963651393519399,"score_spread":0.1917105342133446,"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."}}