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Record W7059975809

Reaching Consumers

2001· article· en· W7059975809 on OpenAlexaboutno aff

Bibliographic record

VenueIowa State University Digital Repository (Iowa State University) · 2001
Typearticle
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipWeb sitePresentation (obstetrics)Food safetyFood supplyRelation (database)Public healthThe InternetFood microbiologyWeb page
DOInot available

Abstract

fetched live from OpenAlex

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.006
GPT teacher head0.155
Teacher spread0.149 · 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.

Study designNot applicable
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
Published2001
Admission routes1
Has abstractyes

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