Probing the pH Dependent Optical Properties of Aquatic, Terrestrial and Microbial Humic Substances by Sodium Borohydride Reduction
Bibliographic record
Abstract
Chemically reducing humic (HA) and fulvic acids (FA) provides insight into spectroscopically identifiable structural moieties generating the optical properties of HA/FA from aquatic, microbial and terrestrial sources. Sodium borohydride reduction provides targeted reduction of carbonyl groups. The contrast between the pH induced optical changes of untreated, reduced and reoxidized HA/FA highlights differences in the quantity, and physicality of structural components generating optical properties associated with HA/FA. Because borohydride reactions alter pH, pH re-adjustment to the original pH is required. Careful titrations of selected HA/FA provided the mmole H+ g-1 HA/FA required to titrate reduced and reoxidized HA/FA from pH 2-11; and the pH dependent spectral slope (S) at low (pH 2-3), neutral (pH 7-7.5) and high (pH 11.0). Molar extinction coefficients (e) (Lmg-1cm-1) at pH 7.6 and 350 nm provide a point of consistency linking intrinsic pH dependent optical properties to the concentration of material used for titrations. Soil derived humic acids differ from aquatic humic acids in the heterogeneity of optically identifiable group as well as the overall concentration of those groups. The microbial source of FA has a limited concentration of homogeneous titratable groups when compared to aquatic FA generated terrestrially. Microbial FA exhibits pH linked optical recovery upon reoxidation when compared to aquatic FA which is consistent with the presence of quinones in microbial FA.
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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 | 0.000 |
| 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 | 0.001 |
| 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".