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Record W7037929336

A generic model for risk-based food inspection in Canada: assessment of initial biological hazards and risk ranking for inspection

2014· dissertation· en· W7037929336 on OpenAlexafffundabout

Bibliographic record

VenueMspace (University of Manitoba) · 2014
Typedissertation
Languageen
FieldEngineering
TopicUrban and Freight Transport Logistics
Canadian institutionsUniversity of Manitoba
FundersPublic Health AgencyPublic Health Agency of CanadaCanadian Food Inspection Agency
KeywordsNucleofectionTSG101HyporeflexiaGestational periodDiafiltrationProteogenomicsDemotionProtein isoform
DOInot available

Abstract

fetched live from OpenAlex

Risk-based inspection provides a framework whereby inspection resources can be prioritized and targeted towards foods that pose the highest risk to human health. To provide a risk assessment of the initial biological hazards associated with foods consumed, criteria related to hazard identification, hazard characterization and exposure assessment were developed for all foods inspected by the Canadian Food Inspection Agency.Using Canadian scientific data, food-pathogen pairs most responsible for foodborne illness were developed and ranked. To characterize the overall population burden of these food-pathogen pairs, a model adapted from the European Food Safety Authority (EFSA) was developed which incorporated criteria related to pathogen characteristics and probability of exposure of humans by food.The top risk-ranked food-pathogen pairs were Campylobacter spp. and poultry, pathogenic Escherichia coli and beef, Salmonella spp. and poultry, Salmonella spp. and produce, and Campylobacter spp. and dairy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.213
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2014
Admission routes3
Has abstractyes

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