Bibliographic record
Abstract
The following report provides a brief overview of extensive studies undertaken in the summer and fall of 2003 to determine the source of Escherichia coli bacteria and the mechanism of transfer to Lake Winnipeg beaches. These studies were undertaken in response to the posting of signs at two Lake Winnipeg beaches for brief periods advising against bathing because of elevated densities of E. coli. These findings will be documented in more detail in a technical report and a manuscript will be prepared for submission to a peer-reviewed, scientific journal. The findings identified in the following report significantly enhance the present understanding of water quality at Lake Winnipeg beaches and the largely natural processes responsible for transferring and dispersing bacteria from the foreshore beach region to bathing water. This phenomenon is likely restricted to large lakes such as Lake Winnipeg due to extensive wave action and daily wind-driven water level fluctuations and likely does not occur to any significant extent on smaller lakes. To the best of the authors ’ knowledge, the findings identified in the following report have not been previously reported from any other large lake situated at this northern temperate latitude in Canada. These findings will allow a greater degree of protection to be provided to public health,
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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.203 | 0.076 |
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".