Conversion of Inorganic Chlorides into Organochlorine Compounds during Crude Oil Distillation: Myth or Reality?
Bibliographic record
Abstract
In this communication, we reinterpreted the experimental findings offered by Wu et al. about the presence and distribution of organic chlorides in crude oil distillates ( Wu, B.; Li, Y.; Li, X.; Zhu, J. Distribution and identification of chlorides in distillates from YS crude oil. Energy Fuels 2015, 29, 1391−1396, 10.1021/ef502450w and Wu, B.; Li, Y.; Li, X.; Zhu, J.; Ma, R.; Hu, S. Organochlorine compounds with a low boiling point in desalted crude oil: Identification and conversion. Energy Fuels 2018, 32, 6475–6481, 10.1021/acs.energyfuels.8b00205). The results proposed by Wu et al. were examined employing a mass balance approach. From our preliminary analysis, we concluded that crude oil distillation may induce (significant) conversions of inorganic chloride into organic chlorides. Such an alteration in chlorine speciation could be relevant for managing corrosion issues in oil refineries.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.002 | 0.008 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".