The microbiology of oil sands tailings: past, present, future
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
Surface mining of enormous oil sands deposits in northeastern Alberta, Canada since 1967 has contributed greatly to Canada's economy but has also received negative international attention due largely to environmental concerns and challenges. Not only have microbes profoundly affected the composition and behavior of this petroleum resource over geological time, they currently influence the management of semi-solid tailings in oil sands tailings ponds (OSTPs) and tailings reclamation. Historically, microbial impacts on OSTPs were generally discounted, but next-generation sequencing and biogeochemical studies have revealed unexpectedly diverse indigenous communities and expanded our fundamental understanding of anaerobic microbial functions. OSTPs that experienced different processing and management histories have developed distinct microbial communities that influence the behavior and reclamation of the tailings stored therein. In particular, the interactions of Deltaproteobacteria and Firmicutes with methanogenic archaea impact greenhouse gas emissions, sulfur cycling, pore water toxicity, sediment biogeochemistry and densification, water usage and the trajectory of long-term mine waste reclamation. This review summarizes historical data; synthesizes current understanding of microbial diversity and activities in situ and in vitro; predicts microbial effects on tailings remediation and reclamation; and highlights knowledge gaps for future research.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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 it