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Infancy, Childhood and Adolescence

2008· book-chapter· en· W191405826 on OpenAlex
Donna Secker

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

VenueNutrition and Health · 2008
Typebook-chapter
Languageen
FieldMedicine
TopicChild Nutrition and Feeding Issues
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMalnutritionMedicinePsychosocialNeurocognitiveAnthropometryKidney diseaseDiseaseIntensive care medicinePediatricsEnvironmental healthPsychiatryInternal medicineCognition

Abstract

fetched live from OpenAlex

Malnutrition in children adversely affects growth and neurocognitive and sexual development; therefore, nutritional management for children with chronic kidney disease focuses on promoting optimal growth and development through maintenance of good nutritional status and prevention of malnutrition, uremic toxicity and metabolic abnormalities. Dietary restrictions are imposed only when clearly needed and are individualized according to age, development and food preferences. Frequent monitoring and adjustments to the nutrition care plan are required in response to changes in the child’s nutritional status, age, development, anthropometrics, food preferences, residual renal function, biochemistries, renal replacement therapy, medications and psychosocial status.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.568
Threshold uncertainty score0.867

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 head0.045
GPT teacher head0.309
Teacher spread0.264 · 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