Novel contaminants identified in fish kills in the Red River watershed, 2011–2013
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 it