Compartmentalization of Metals within the Diverse Colloidal Matrices Comprising Activated Sludge Microbial Flocs
Bibliographic record
Abstract
Activated sludge floc from a wastewater treatment system was characterized, with regard to principal structural, chemical, and microbiological components and properties, in relation to contaminant-colloid associations and settling. Multiscale analytical microscopies, in conjunction with multimethod sample preparations, were used correlatively to characterize diverse colloidal matrices within microbial floc. Transmission electron microscopy, in conjunction with energy dispersive spectroscopy (EDS), revealed specific associations of contaminant heavy metals with individual bacterial cells and with extracellular polymeric substances (EPS). Floc structure was mapped from the level of gross morphology down to the nano-scale, and flocs were described with respect to settling properties, size, shape, density, porosity, bound water content, and EPS chemical composition; gross surface properties were also measured for correlation with principal floc features. Compartmentalization results based on 171 EDS analyses and representative high-resolution images showed that nano-scale agglomerations of (i) silver (100%) and (ii) zinc (91%) were confined almost entirely to EPS matrices while (iii) Pb (100%) was confined to intracellular granules and (iv) aluminum was partitioned between EPS matrices (41%) and intracellular matrices (59%). The results suggest that engineered changes in microbial physiology and/or in macromolecular EPS composition may influence metal removal efficiencies.
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.001 | 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 teacher head, 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".