Novel contaminants identified in fish kills in the Red River watershed, 2011–2013
Bibliographic record
Abstract
Abstract Provisional molecular weights and chemical formulas were assigned to 4 significant previously unidentified contaminants present during active fish kills in the Red River region of Oklahoma. The provisional identifications of these contaminants were determined using high-resolution liquid chromatography–time-of-flight mass spectrometry (LC-TOFMS), LC-Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICRMS), and LC-ion trap mass spectrometry (LC-ITMS). Environmental water samples were extracted using a solid-phase extraction (SPE) method, and sediment samples were extracted using a modified sonication liquid extraction method. During screening of the samples, 2 major unknown chromatographic peaks were detected at m/z 624.3 and m/z 639.3. The peak at m/z 639.3 was firmly identified, through the use of an authentic standard, as a porphyrin, specifically chlorin-e6-trimethyl ester, with m/z 639.31735 (M + H)+ and molecular formula C37H43N4O6. The other major peak, at m/z 624.3 (M + H)+, was identified as an amide-containing porphyrin. It was discovered that the amide compound was an artifact created during the SPE process by reaction of ammonium hydroxide at 1 of 3 potential reaction sites on chlorin-e6-trimethyl ester. Other unique nontargeted chemicals were also detected and the importance of their identification is discussed. Environ Toxicol Chem 2018;37:336–344. Published 2017 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America. Abstract
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".