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Record W2608178729 · doi:10.1002/cpt.677

Adverse Drug Reactions in Children: The Double‐Edged Sword of Therapeutics

2017· review· en· W2608178729 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

VenueClinical Pharmacology & Therapeutics · 2017
Typereview
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineDrug reactionEpidemiologyDrugIntensive care medicinePopulationIncidence (geometry)PediatricsPharmacologyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Adverse drug reactions (ADRs) represent a major health problem worldwide, with high morbidity and mortality rates. ADRs are classified into Type A (augmented) and Type B (bizarre) ADRs, with the former group being more common and the latter less common but often severe and clinically more problematic due to their unpredictable nature and occurrence at any dose. Pediatric populations are especially vulnerable to ADRs due to the lack of data for this age group from the drug development process and because of the wide use of off-label and unlicensed use of drugs. Children are more prone to specific types of ADRs because of the level of maturity of body systems involved in absorption, metabolism, transportation, and elimination of drugs. This state-of-the-art review provides an overview of definitions, classifications, epidemiology, and pathophysiology of ADRs and discusses the available evidence for related risk factors and causes of ADRs in the pediatric population.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
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 head0.461
GPT teacher head0.587
Teacher spread0.126 · 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