Wastewater discharges alter microbial community composition in surface waters of the Canadian prairies
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
Freshwater ecosystems occupy only a small portion of the Earth's surface, but harbor a disproportionate amount of biodiversity that is particularly threatened by wastewater discharges, as one of the most common anthropogenic impact on these systems. As wastewater effluents are also sources of antimicrobial agents and other microorganisms, they reflect a particular threat to natural microbial communities within receiving rivers. Our knowledge about the impact of wastewater effluents on these communities is, however, largely unexplored. In this study, composition of microbial communities upstream and downstream of 5 different wastewater treatment plants within Southern Saskatchewan, Canada were examined. Three matrices, the water column, sediments, and biofilms attached to hard surfaces, were analyzed. The samples were extracted for DNA and were PCR amplified targeting the hypervariable V3-V4 region of the 16S ribosomal RNA subunit I gene of prokaryotes, as well as the hypervariable V3 region of the 18S ribosomal RNA gene of eukaryotic organisms. Amplicons were sequenced performing a 600-cycle paired-end sequencing run on an Illumina® MiSeq sequencer. This dataset includes the demultiplexed sequencing output, the feature table with taxonomic annotation, and the sample metadata.
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.
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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.000 | 0.003 |
| 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 it