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Record W4386751852 · doi:10.51731/cjht.2023.736

Somatropin for Short Stature

2023· article· en· W4386751852 on OpenAlexaboutno aff
Camille Santos, Jennifer Horton

Bibliographic record

VenueCanadian Journal of Health Technologies · 2023
Typearticle
Languageen
FieldMedicine
TopicGrowth Hormone and Insulin-like Growth Factors
Canadian institutionsnot available
Fundersnot available
KeywordsIdiopathic short statureGuidelineShort statureMedicineGrowth hormoneContext (archaeology)SomatropinPediatricsGrowth hormone treatmentSmall for gestational ageHormoneEndocrinologyIntensive care medicineGestational ageBiologyPregnancyPathology

Abstract

fetched live from OpenAlex

For children with short stature who were born small for gestational age, 1 guideline suggests increasing human growth hormone dose when treatment response is unsatisfactory, while aiming for normal insulin-like growth factor 1 levels. For children with idiopathic short stature, 1 guideline recommends against the routine use of growth hormone. It suggests initiating growth hormone therapy on a case-by-case basis, with a starting dose ranging from 0.24 mg/kg/week to 0.47 mg/kg/week, as well as conducting an assessment 12 months after initiation to optimize dosage. The development of recommendations from guidelines included in this report was challenged by limited relevant evidence, as well as heterogeneity of growth hormone dose and frequency and treatment response found in available literature. Future guidelines should also consider patient perspectives, resource implications, and the facilitators of and barriers to therapy within the context of health care systems in Canada.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.080
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.003

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 head0.051
GPT teacher head0.323
Teacher spread0.271 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Health TechnologiesSame topicGrowth Hormone and Insulin-like Growth FactorsFrench-language works237,207