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Record W2129236569 · doi:10.12927/hcq.2013.21121

CIHI Survey: Hospital Costs for Preterm and Small-for-Gestational Age Babies in Canada

2009· article· en· W2129236569 on OpenAlexaffabout
Gillian Lim, Jacinth Tracey, Nicole Boom, Sunita Karmakar, Joy Wang, Jean‐Marie Berthelot, Caroline Heick

Bibliographic record

VenueHealthcare Quarterly · 2009
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsCanadian Institute for Health Information
Fundersnot available
KeywordsMedicineBirth weightGestational ageSingletonLow birth weightSmall for gestational agePediatricsObstetricsPregnancy

Abstract

fetched live from OpenAlex

In 2006-2007, more than 54,000 (or one in seven) babies across Canada were born preterm or small for their gestational age (SGA). These babies are often at higher risk for morbidity and mortality than are full-term babies with normal birth weight, and account for a disproportionately high percentage of healthcare costs among newborns. This article highlights key findings from a recent report by the Canadian Institute for Health Information, Too Early, Too Small: A Profile of Small Babies across Canada, and provides information on the hospital costs among low birth weight, preterm and SGA babies. Birth weight and gestational age were found to be important determinants of hospital costs - as birth weight and gestational age decreased, average in-hospital costs increased. Furthermore, multiple-birth babies had higher hospital costs than did singleton babies. As in other areas of the health system, information relating to costs and spending can inform neonatal and obstetrical health planning and decision-making.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.361
Teacher spread0.317 · 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 designObservational
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

Citations52
Published2009
Admission routes2
Has abstractyes

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