{"id":"W4313471174","doi":"10.3390/toxins15010027","title":"A Feasibility Study into the Production of a Mussel Matrix Reference Material for the Cyanobacterial Toxins Microcystins and Nodularins","year":2022,"lang":"en","type":"article","venue":"Toxins","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"Interreg; Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; Centre for Environment, Fisheries and Aquaculture Science","keywords":"Cyanotoxin; Mussel; Cyanobacteria; Chromatography; Certified reference materials; Shellfish; Liquid chromatography–mass spectrometry; Chemistry; Domoic acid; Microcystin; Mass spectrometry; Matrix (chemical analysis); Environmental chemistry; Biology; Toxin; Detection limit; Biochemistry; Fish <Actinopterygii>; Aquatic animal; Fishery","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":[],"consensus_categories":[],"category_scores_codex":[0.0009037887,0.0001207599,0.0001660156,0.00001368174,0.0006272143,0.00003580123,0.0003333807,0.00002665273,0.0005874875],"category_scores_gemma":[0.000111742,0.00007418593,0.00003921061,0.0001365317,0.0001276819,0.00006850754,0.0004476919,0.0001144038,0.000006042801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001406971,"about_ca_system_score_gemma":0.00002360644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002268799,"about_ca_topic_score_gemma":0.006242767,"domain_scores_codex":[0.9988217,0.0001616408,0.0002907888,0.0003209363,0.0002376235,0.0001672526],"domain_scores_gemma":[0.9991752,0.0001353681,0.0001691722,0.0004756126,0.00001349515,0.00003119028],"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":[0.00258297,0.00308609,0.2269102,0.0002386783,0.0002129393,0.000005941361,0.06107395,0.003206731,0.6918199,0.001956458,0.002911257,0.005994891],"study_design_scores_gemma":[0.003935724,0.004302391,0.8535035,0.0000374194,0.0004812493,0.0001519126,0.0329814,0.01126294,0.01449563,0.002092133,0.07566683,0.001088883],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965332,0.000009948509,0.0001138352,0.0004635092,0.0006874738,0.001891134,0.0001645405,0.00001798001,0.0001183643],"genre_scores_gemma":[0.9989374,0.000003925122,0.0002169103,0.00003980167,0.0001092196,0.000249988,0.00001473549,0.00001154916,0.0004165165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6773243,"threshold_uncertainty_score":0.6432577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01882381398664798,"score_gpt":0.2597569813339533,"score_spread":0.2409331673473053,"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."}}