Bibliographic record
Abstract
Johnson, who demonstrated the importance of asking questions of value and questioning what is presented as the truth, and to Murray Johnson who helped me to realize that discovery can be a creative process. This is also dedicated to the memories of Robin Costain and Carl Nishi. m E. coli 0157:H7 were isolated from 0.86 % (n=1520) water samples and Salmonella species from 6.04 % (n=1456) samples collected within the Oldman River watershed in southern Alberta. Peak prevalence of E. coli 0157:H7 in July 2000 was 6.3 % {n =48). Peak prevalence of Salmonella was 16.2 % (n =11) in August 1999 and 33. % (n=42) in July 2000. Prevalence was greater in water from some sampling locations than from others. In non-filtered surface water E. coli 0157:H7 and S. typhimurium numbers decreased significantly faster at 20 °C than at 10 °C (P =0.000); however this difference did not exist when the same water was filtered (P=0.439). Pathogen survival in one water sample was greater when it was filtered (0.2jxm pore) than when it was not filtered
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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.298 | 0.125 |
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".