{"id":"W2034999399","doi":"10.1016/j.chroma.2009.06.050","title":"Analysis of trace levels of domoic acid in seawater and plankton by liquid chromatography without derivatization, using UV or mass spectrometry detection","year":2009,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Marine Toxins and Detection Methods","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"Fisheries and Oceans Canada; Dalhousie University; Institute for Marine Biosciences","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Atlantic Canada Opportunities Agency; Canadian Food Inspection Agency","keywords":"Chromatography; Chemistry; Derivatization; Detection limit; Domoic acid; Seawater; Mass spectrometry; Sample preparation; Liquid chromatography–mass spectrometry; Extraction (chemistry); Elution; Solid phase extraction","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002257816,0.0004083342,0.0002587958,0.0004490172,0.0004612005,0.0004130742,0.0002404122,0.000386239,0.0005076373],"category_scores_gemma":[0.0004236281,0.0002034448,0.0001352226,0.0002846425,0.0002940763,0.0003002583,0.0003206038,0.0003736504,0.0003000603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003013375,"about_ca_system_score_gemma":0.0006123208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002174815,"about_ca_topic_score_gemma":0.003293327,"domain_scores_codex":[0.9998092,0.00002637893,0.00001474915,0.00005145368,0.00007189167,0.00002636366],"domain_scores_gemma":[0.9998007,0.00006359132,0.00002236561,0.00001602586,0.00005206806,0.00004518073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002412212,0.00002088403,0.002621674,0.0000258736,0.000007108424,0.00002955433,0.00002349894,0.00003239952,0.993897,0.00002861582,0.00001671363,0.00305537],"study_design_scores_gemma":[0.00001889181,0.0002605609,0.01173724,0.000007057185,0.00002476725,0.0001335607,0.00004742366,0.000926452,0.9856851,0.00006581738,0.001084295,0.000008821314],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9856227,0.001208675,0.01089876,0.00007178828,0.00003653107,0.00003978737,0.0004993765,0.00008294346,0.001539412],"genre_scores_gemma":[0.9698945,0.001427652,0.022862,0.0001320549,0.00003037636,0.00009518427,0.0008656586,0.0000283333,0.004664292],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002174815,"threshold_uncertainty_score":0.004324257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01301980465370484,"score_gpt":0.2684090639241105,"score_spread":0.2553892592704056,"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."}}