Bringing Jesus to the Desert: Uncover the Ancient Culture, Discover Hidden Meanings by Bradley Nassif (review)
Bibliographic record
Abstract
Pollution has been less investigated in marine and coastal environments than in inland waters. The low levels at which pollutants are expected to be present in seawater calls for the use of reliable and high sensitivity analytical methodologies. In this context, this work presents the optimization and validation of an analytical method to determine 26 medium to highly polar pesticides in seawater based on solid phase extraction and liquid chromatography-tandem mass spectrometry detection. The developed methodology was linear, accurate (relative recoveries within 80-120% for most analytes), repeatable (relative standard deviations <18% for most analytes), and sensitive (limits of determination <1 ng/L for 89% of the compounds). The use of isotopically labeled compounds as surrogate standards compensated for low analyte recoveries and matrix effects. The method was applied to the analysis of seawater samples collected along the coastline of Catalonia (NE Spain). Overall, total pesticide loads were higher inside the marinas than outside. The booster biocides diuron and irgarol used in antifouling paintings and different triazine pesticides were the most abundant compounds. Irgarol was present above the maximum allowable concentration set in European regulations in 70% of the samples collected inside the marinas. A different pesticide pollution pattern, with MCPA and bentazone presenting the highest concentrations, was observed at the Ebro Delta area due to the impact of the agricultural activities carried out there. To the authors' knowledge, 4 out of the 26 target pesticides, namely, chlorfenvinphos, fenthion oxon, fenthion sulfone, and fenthion sulfoxide, have not been previously investigated in seawater.
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How this classification was reachedexpand
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".