Comparison of Real Versus Synthetic <scp>NOM</scp> on Lead and Copper Release Using Dump and Fill Studies
Bibliographic record
Abstract
ABSTRACT The main objective of this study was to evaluate and compare the impact of real and synthetic NOM on lead and copper release from galvanic corrosion. A 21‐week “dump and fill” experiment was completed using test pieces with new lead and copper pipes exposed to various drinking waters. The real waters consisted of unchlorinated, but otherwise conventionally treated, river water and raw municipal well water. Each real water was simulated using two synthetic waters: one with Suwannee River NOM (SRNOM) at the same DOC concentration as in the real water and another without NOM. The synthetic waters with SRNOM released the most dissolved lead, followed by the real waters, and finally by the synthetic waters without SRNOM. Using advanced techniques of characterizing colloidal lead and NOM, complexation was found to be responsible for much of the NOM‐induced dissolved lead release, and humic substances were the component that complexed most strongly.
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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 | 0.001 | 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".