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Record W1973505151 · doi:10.4141/a03-098

Frankfurters — acceptability under different retail lights

2004· article· en· W1973505151 on OpenAlexaffvenue
Shai Barbut

Bibliographic record

VenueCanadian Journal of Animal Science · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsFood scienceChemistryIncandescent light bulbLuminanceSignificant differenceFluorescent lightFluorescenceOpticsMathematicsPhysics

Abstract

fetched live from OpenAlex

Dark, medium, and light colour frankfurters (no-fat, low-fat, and regular fat level) were evaluated by panellists under incandescent (INC), fluorescent (FL), and metal halide (MH) light sources. INC illumination resulted in a higher colour preference (P < 0.05) for the medium and light products over that of the FL and MH illuminations; no significant difference was seen between FL and MH lighting. The panellists described the medium coloured frankfurters as pink under INC lighting, but more brown under FL and MH illumination. Relative luminance data, collected via a fibre optic probe connected to a photo diode array, demonstrated the reason to be the low red colour seen by the panellists under FL and MH light sources. For the dark colour frankfurters, there was no difference in colour preference scores among the three illumination sources. Key words: Colour, fat, frankfurters, light, meat, sausage, sensory, spectra

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.047
GPT teacher head0.245
Teacher spread0.198 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2004
Admission routes2
Has abstractyes

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