Relative importance of organic- and iron-based colloids in six Nova Scotian lakes
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 Dissolved organic matter (DOM) concentrations have been increasing in parts of the northern hemisphere for several decades. This process—brownification—often accompanies increasing iron and aluminum, but the metal–DOM interactions these concurrent trends imply are poorly described. Here we used field-flow fractionation with UV and ICP-MS detection to measure the size distribution of colloidal iron, aluminum, manganese, copper, uranium, and chromophoric DOM in six lakes over six months. Five of these lakes have browned to some degree in the past three decades, with linear increases in organic carbon and color ranging from 0.01 to 0.13 mg C L −1 yr −1 and 0.13–1.94 PtCo yr −1 . Browning trends were more pronounced and colloids more abundant in lakes with wetlands in their catchments. Iron and aluminum were present in two primary fractions, sized nominally at 1 and 1000 kDa. The 1 kDa fraction included the primary DOM signal, while the 1000 kDa fraction absorbed minimally at 254 nm and likely represents iron-rich (oxyhydr)oxides. Colloidal manganese was sized at 1000+ kDa, whereas colloidal copper and uranium occurred primarily at 1 kDa. These associations fit with a pattern of increasing DOC, iron, aluminum, and color in the region’s lakes. They represent a significant challenge for drinking water treatment systems, especially those in remote communities. Given that browning trends are expected to continue, monitoring plans would better inform treatment process design and operation by characterizing DOM and iron-rich, primarily inorganic colloids that contribute to adverse water quality outcomes.
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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 | 0.000 |
| 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) | 0.006 | 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