Bibliographic record
Abstract
The Food Safety Consortium (FSC) Web site project has expanded its content significantly this past year with new initiatives, a full set of HACCP procedures with examples for small meat processors and a biotechnology section. A presentation on biotechnology has been downloaded more than 300 times since its posting in a 3 month period. We have continued our partnership with the University of Guelph, Ontario, Canada, to provide daily international food safety news from newswires and scientific journals. More than 38,000 consumers have accessed and completed one of the four interactive food safety lessons. Additionally, more than 264,000 consumers had 467,000 page views accessed through the Food Safety Web site home page or one of its links for a total of 2,744,880 hits last year. Visitors from 77 countries accessed our site and used our information about the source, symptoms, and methods of preventing Staphylococcus, Salmonella, and Listeriosis. Companies or net providers accounted for 71% of the hits. Users visited the site for an average of 10-1/2 minutes per session, far above average. Improve understanding of risks and responsible practices in relation to food and health through increased knowledge. Maintain and enhance presence of Food Safety Consortium Web at www.foodsafety.iastate.edu/. Post research findings on the Consortium Web site as they become available. www.foodsafety.iastate.edu/ and links to www.extension.iastate.edu/foodsafety/.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.297 | 0.184 |
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".