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Record W1980574676 · doi:10.3148/70.4.2009.200

<i>Transformation to Room Service Food Delivery</i> In a Pediatric Health Care Facility

2009· article· en· W1980574676 on OpenAlexaffvenueabout
Karen Kuperberg, Diana R. Mager, Susan Dello

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2009
Typearticle
Languageen
FieldMedicine
TopicChild Nutrition and Feeding Issues
Canadian institutionsUniversity of AlbertaSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsService (business)Work (physics)Multidisciplinary approachBusinessNursingService delivery frameworkMedicineProcess (computing)Operations managementMedical emergencyMarketingEngineeringComputer science

Abstract

fetched live from OpenAlex

Patient food service is an important component in the nutritional management of hospitalized children. The previous meal delivery system at The Hospital for Sick Children in Toronto was a cold-plating re-thermalized system. Issues related to this model included order lead time, the reheating process, menu selection, and service style. Research into other systems led us toward room service, an innovative and flexible mode of meal delivery. Transformation to room service occurred over one year, and included implementation of a new computer system, kitchen renovation, redesign of menus and a new meal delivery system called Meal Train, and changes to human resource allocations. Throughout the transformation, consultations were held with key stakeholders, including the children's council, the family advisory, the nursing council, and a multidisciplinary committee involving nursing staff, dietitians, patient service aides, infection control personnel, occupational health employees, patient representatives, and food services staff. Now, Meal Train is running smoothly, and meal days and food costs have been reduced. Others considering a project like this must know their clients' needs and be willing to think outside the box. They should familiarize themselves with current information on systems and equipment, consult with key stakeholders within their organization, and then create the system that will work for them.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.066
GPT teacher head0.384
Teacher spread0.318 · 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 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

Citations11
Published2009
Admission routes3
Has abstractyes

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