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Record W2040443907 · doi:10.1080/10942910802312157

Textural Characterization of Pureed Cakes Prepared for the Therapeutic Treatment of Dysphagic Patients

2009· article· en· W2040443907 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Food Properties · 2009
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsMcGill UniversityAir Canada
Fundersnot available
KeywordsDysphagiaFood scienceTherapeutic effectMedicineChemistrySurgery

Abstract

fetched live from OpenAlex

Dysphagia is a difficulty in eating and swallowing of solid and/or liquid foods in elderly patients. Texture characterization of therapeutic diets for dysphagia patients has not been studied extensively. In this study, five different pureed therapeutic cakes (apple, orange, vanilla, carrot, and chocolate), previously proved efficient in the treatment of dysphagic patients, were evaluated for firmness, cohesiveness, adhesiveness, and springiness using textural profile analysis. The therapeutic cakes were tested at two serving temperatures: 12°C and 23°C. Results of sensorial tests confirmed that clinical efficiency and texture firmness of the therapeutic cakes ranged from 0.741 to 2.52 N for cakes at 12°C and from 0.608 to 2.58 N for cakes at 23°C. Similarly, cohesiveness ranged from 0.391 to 0.561 at 12°C and 0.479 to 0.568 at 23°C, adhesiveness from –0.219 to –0.436 N at 12°C and – 0.201 to –0.424 N at 23°C and finally springiness ranged from 46 to 70% at 12°C and 24 to 61% at 23°C. Non-therapeutic cakes averaged 2.77 N for firmness, 0.553 for cohesiveness, –0.385 N for adhesiveness, and 55% for springiness.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.211

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 head0.072
GPT teacher head0.375
Teacher spread0.303 · 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