Investigation of Effects of the Cosolvent Methanol on the Apparent Solubility of a Suite of Chlorobenzenes Using Headspace Solid-Phase Microextraction (HS-SPME)
Bibliographic record
Abstract
Cosolvent effects have historically been considered as negligible at cosolvent spiking concentrations below 1 %. Headspace solid-phase microextraction (HS-SPME) was used to determine the effect of the cosolvent methanol (MeOH) on apparent solubility of three chlorobenzenes (CBs) (1,2,4,5-tetrachlorobenzene, pentachlorobenzene, and hexachlorobenzene). All CBs exhibited a ln-linear decreasing relationship between cosolvent volume fraction and extracted mass. However, there were no statistical differences in measured headspace CB concentration at cosolvent additions of 1 % or less compared to controls. This study validated the use of MeOH volumes of 1 % and lower for batch studies using HS-SPME. Ninety-six hour incubation studies using 0.01 %, 10 %, and 100 % MeOH treatments demonstrated chemical losses from headspace vials through time. Declines were greatest for 0.01 % MeOH treatments and nonsignificant for vials containing 100 % MeOH. The silanization of vials using 5 % DCMCS was unsuccessful in reducing chemical loss; therefore potential loss processes must be further investigated prior to using the HS-SPME method for incubated treatments.
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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 | 0.001 |
| 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 | 0.000 | 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".