Kinetics of phytoremediation of petroleum hydrocarbon contaminated soil
Bibliographic record
Abstract
Earthmaster and the University of Waterloo have successfully developed plant growth promoting rhizobacteria (PGPR) - Enhanced Phytoremediation Systems (PEPSystems™) which have been deployed across Canada for the treatment of soil contaminated with petroleum hydrocarbons (PHCs), including CCME fractions F2 and F3. A challenge with phytoremediation is to predict the length of time to remediate a site so that site owners will be inclined to use the technology. In previous field trials of PEPSystems, it was determined that PHC was mostly degraded by microbes in the rhizosphere, following first-order exponential decay kinetics. Using new PEPSystems data collected from multiple commercial remediation sites across Western Canada, the kinetic equations of PHC decay were tested to determine if remediation time was accurately predicted. In general, when compared to the predicted time to remediation endpoint, data from recent commercial field applications showed that 35% and 20% less time was needed to reach remediation endpoints for fractions F2 and F3, respectively. As a result, the predictive kinetic equation for fraction F2 degradation was updated to reflect current remediation outcomes. Insufficient data were available to update the F3 equation. Being able to more accurately predict remediation timelines will enhance the value and utilization of PEPSystems.
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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 | 0.000 | 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) | 0.001 | 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".