Examination of the food safety system in the state of Qatar / by Allan Stirling
Bibliographic record
Abstract
Foodbome illness continues to be endemic in our global environment. Protecting the \nhuman host from exposure to foodbome pathogens and reducing the incidence of foodbome \nillness are the central goals of established food safety intervention programs at national levels. \nFoodbome illness is a significant contributor to morbidity figures and has a major economic \nimpact on global health care systems. For example, foodbome surveillance activities in the \nUnited States state that, "foodbome illnesses affect 6 to 80 million persons, cause 9, 000 deaths \nand cost an estimated 5 billion U.S. dollars annually? (Altekmse, Cohen, Swerdlow, 1997). \nMoreover, the consequences of foodbome illness in the public food service sector have an \nimpact on foodservice workers, the foodservice industry and the community. \nIf a business is implicated in a case of foodbome illness it can result in financial loss \nbecause of bad publicity and the subsequent loss of business, increased insurance premiums, a \nloss of consumer trust in the food supply and distrust in public health authorities responsible for \nthe protection of population health. ?In Canada, as many as 8.5 million Canadians \n(approximately 1 in 4 persons) are estimated to develop foodbome illness resulting in the \nhospitalization of 39 000 people and as many as 600 deaths? (Canadian Restaurant and \nFoodservices Association, 2003). The resultant burden on the health care system has been \nestimated at approximately 2 billion dollars annually (Canadian Restaurant and Foodservices \nAssociation, 2003). ?The majority of enteric disease is mild and requires only a day or two of \nreduced activities; however, these cases pose a significant burden due to lost of productivity and \nother related costs. In Ontario, about 1 in 313 cases of enteric disease are reported to the province through passive disease surveillance? (Majowicz, et al., 2004) suggesting that many \ncases are overlooked or ignored.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".