A longitudinal study of feed contamination by European starling excreta in Ohio dairy farms (2007–2008)
Bibliographic record
Abstract
The objectives of this study were to understand the temporal pattern of contamination of cattle feed by starling excrement on dairy farms and to evaluate the temporal pattern in recovering Escherichia coli O157:H7 or Salmonella in relation to the absolute mass of excrement recovered. A longitudinal study was conducted on 15 dairy farms in Ohio from July 2007 to October 2008. One open-topped tray filled with bird feed was placed near a cattle feeding site; bird excrement from the tray was weighed monthly for 12 consecutive months. Linear regression models with a random intercept for farm were computed to examine the association between the absolute weight of excrement recovered each month or the farm-specific standard score for weight of excrement, and month or season. Exact logistic regression was used to determine whether an association between recovering E. coli O157:H7 or Salmonella was present and the amount of excrement recovered and season. A spatial scan statistic was used to test for evidence of space-time clustering of excrement, based on the standard score for the weight of the excrement, among our study farms. A total of 5 of 179 excrement samples (2.79%) were positive for E. coli O157:H7 and 2 (1.12%) were positive for Salmonella. A significantly higher level of contamination with excrement was observed during the winter. The odds of recovering a pathogen increased with the amount of excrement recovered and decreased if the excrement was collected in the winter. A spatio-temporal cluster of contamination with excrement was detected. These findings provide basic information for future quantitative microbial risk assessments concerning the role of starlings in spreading enteric pathogens on dairy farms.
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 | 0.001 | 0.001 |
| 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 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".