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Record W2204642778 · doi:10.5539/jfr.v5n1p49

Consumer Responses to Proposed Instructions for Cooking Mechanically Tenderized Beef Steaks

2015· article· en· W2204642778 on OpenAlexvenueaboutno aff
Mark D. Klassen, C.O. Gill

Bibliographic record

VenueJournal of Food Research · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Safety and Hygiene
Canadian institutionsnot available
Fundersnot available
KeywordsFood scienceBusinessBiology

Abstract

fetched live from OpenAlex

Mechanical tenderizing of beef can result in bacteria, which may include enteric pathogens such as <em>Escherichia coli</em> O157:H7, from the surface being carried into previously sterile deep tissues. A telephone survey of 1021 Canadian consumers was conducted during September 2013 to determine current steak cooking practices, and responses to proposed instructions for cooking to ensure microbiological safety intended for labels on packs of mechanically tenderized beef (MTB) steaks. The responses indicated that 95% of Canadian consumers preferably cook steaks to a medium rare or more well done condition while 66% turn steaks over twice or more during cooking. These practices are those required to ensure the microbiological safety of MTB steaks. Apparently, over 80% of consumers would have no difficulty understanding, and would be likely to follow instructions that specify these practices for the safe cooking of MTB steaks.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.243

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.284
GPT teacher head0.387
Teacher spread0.103 · 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 designBench or experimental
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

Citations5
Published2015
Admission routes2
Has abstractyes

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