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 Disinfection by‐products (DBPs) were detected in drinking water over 35 years ago. Since then identification of DBP species has closely paralleled advances in analytical chemistry. Today over 600 individual DBP species, representing several chemical classes, have been identified in drinking water. Potential DBP health concerns reported by some toxicology and epidemiology studies include elevated risks of developing certain cancers or adverse reproductive outcomes. New drinking water regulations must be evidence‐based, requiring next‐generation DBP studies that better link advances in analytical methods with a focus on DBPs that have the biological plausibility to cause the adverse outcomes we seek to avoid. The strategic development of the nationwide DBP occurrence study in the United States has helped to refocus today's global DBP research agenda toward a new generation of emerging DBPs of health significance. Notable DBP classes now being studied include: halonitromethanes, haloamides, halogenated furanones, haloaldehydes, haloquinones, as well as N‐nitrosamines and iodo‐DBPs. Improvements in extraction, separation, and detection technologies have improved our ability to identify DBP species that were once difficult, if not impossible, to detect by gas chromatography methods. Liquid chromatography/mass spectrometry applications are providing new insights into the monitoring of nonvolatile, high‐molecular‐weight, highly polar, hydrophilic, and thermally labile target compounds in drinking water. On‐line monitoring and expanded studies evaluating swimming pool exposures are the latest innovations in the ongoing interdisciplinary research related to the analysis of emerging DBPs.
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 | 0.001 |
| 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) | 0.017 | 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