Comparison of the catabolic activity and catabolic profiles of rhizospheric, gravel-associated and interstitial microbial communities in treatment wetlands
Bibliographic record
Abstract
Microbial communities play a critical role in degrading organic contaminants in treatment wetlands; however, an understanding of the different roles played by rhizospheric, gravel-associated and interstitial microbial communities is deficient due to a lack of data directly comparing these microbial communities. Community level physiological profiling (CLPP) was used to compare the catabolic capabilities of rhizospheric, gravel-associated and interstitial microbial communities in vertical-flow planted and unplanted wetland mesocosms. Wetland mesocosms were decommissioned to gather microbial community samples associated with the roots and gravel bed media taken from the top (10 cm depth), middle (30 cm depth) and bottom (60 cm depth). The catabolic capabilities of the rhizospheric microbial communities were seen to be much greater than those of the gravel-associated communities. A decrease in catabolic capability was seen with increasing depth, suggesting that communities near the surface play a larger role in the degradation of carbon-based compounds. A general difference in catabolic profiles based on plant presence/absence was observed for the interstitial water and all gravel-associated samples at all depths, suggesting that the presence of roots within part of the mesocosm not only has a localized effect on the attached microbial population, but also on gravel-associated microbial communities throughout the mesocosms.
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.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".