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INSTRUMENTAL MEASURES OF BITE FORCES ASSOCIATED WITH CRISP PRODUCTS

2006· article· en· W1980153010 on OpenAlexaff
Lisa M. Duizer, Ray J. Winger

Bibliographic record

VenueJournal of Texture Studies · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsAcadia University
Fundersnot available
KeywordsBite force quotientBrittlenessBitingMaterials scienceComposite materialStress (linguistics)OrthodonticsMedicineGeology

Abstract

fetched live from OpenAlex

ABSTRACT The usefulness of a bite force apparatus for measuring bite forces generated while biting extruded crisp snacks was assessed. Snacks were produced using a twin‐screw extruder, and their textural properties were modified by equilibrating to water activities ranging from 0.11 to 0.44. Maximum force to bite, stress, duration and area under the bite force curve were analyzed and compared to perceived sensory crispness, hardness, brittleness and sound duration evaluated by eight individuals. Maximum bite force and stress were significantly related to hardness, brittleness and crispness showing for the first time, and the relationship between sensory crispness of extruded crisp products and hardness was measured intraorally.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.237
Teacher spread0.214 · 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

Citations41
Published2006
Admission routes1
Has abstractyes

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