pK<sub>a</sub>values of the monohydroxylated polychlorinated biphenyls (OH-PCBs), polybrominated biphenyls (OH-PBBs), polychlorinated diphenyl ethers (OH-PCDEs), and polybrominated diphenyl ethers (OH-PBDEs)
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
The SPARC software program aqueous pK(a) prediction module was validated against corresponding experimental acidity constants for chlorinated and brominated phenols and the limited experimental aqueous pK(a) data sets for monohydroxylated polychlorinated biphenyls (OH-PCBs), polychlorinated diphenyl ethers (OH-PCDEs), and polybrominated diphenyl ethers (OH-PBDEs). pK(a) values were then estimated for all 837 monohydroxylated mono- through nona-halogenated congeners in each of the OH-PCB, OH-PCDE, and OH-PBDE classes, as well as for the monohydroxylated polybrominated biphenyls (OH-PBBs), giving a total of 3348 compounds. Large intrahomolog pK(a) variation by up to six units is expected within each contaminant class, with pK(a) values ranging from about 4 to 11 dependent on the degree and pattern of halogenation. Increasing halogenation generally decreased the average pK(a) within each homolog group. Significant intrahomolog differences in pK(a) values exist between OH-PCB, OH-PBB, OH-PCDE, and OH-PBDE congeners, including large acidity constant variation between isomers with equivalent halogenation patterns but varying location of the hydroxy moiety. Congener specific pH dependent investigations into the partitioning and degradation behaviors of these compounds are necessary, including greater consideration of analyte ionization effects during their extraction and analysis.
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 it