Bibliographic record
Abstract
Conventional culvert designs based on hydraulic capacity often result in high velocities or inadequate water levels that are not conducive for fish migration. For fish-bearing stream crossings, alternative designs need to be developed in order to secure timely approval from Fisheries and Oceans Canada (DFO). Stream simulation is one of those alternatives. It was proposed to, and accepted by, DFO for the Conn Creek Culvert replacement in Fort McMurray, an environmentally sensitive site due to the controversy over Alberta oil sand projects. The existing 4.2 m diameter, 82 m long culvert carries four lanes of Highway 63 traffic across Conn Creek, a tributary to the Athabasca River. As part of the $530 million Highway 63:11 upgrading project, the existing culvert required extension. During the review of the proposed alternatives, DFO cited the high flow velocity within the existing culvert as a barrier to fish passage, resulting in the separation of upstream and downstream habitats. Authorization for the works would need to ensure fish passage was restored. This paper presents the background of the project, the existing fisheries, and details of the stream simulation design used to satisfy regulatory and project requirements. It is also the authors' intention to share their experiences and lessons learned in securing a timely approval from DFO on an extremely tight schedule. For the covering abstract of this conference see ITRD record number 201211RT334E.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".