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Record W1485407772 · doi:10.1002/ppul.22657

Nanomedicine as an innovative therapeutic strategy for pediatric lung diseases

2013· article· en· W1485407772 on OpenAlexaff
Ye Tian, Jian Chen, Fatemeh Zahtabi, Richard Keijzer, Malcolm Xing

Bibliographic record

VenuePediatric Pulmonology · 2013
Typearticle
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsResearch ManitobaUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
Fundersnot available
KeywordsNanomedicineMedicineNanotechnologyDrug deliveryNanoparticleMaterials science

Abstract

fetched live from OpenAlex

Nanomedicine is a rapidly emerging technology and represents an innovative field for therapy. Nanomaterials have intrinsically defined features for biomedical applications due to the high specific surface area, the amazing diversity, versatility in structure and function and the possibility of surface charge. In particular, the functionalization of targeting or stimuli-responsive unit on the surface of these materials gives them specific targeted therapeutic properties. There are many pediatric lung diseases that could potentially benefit from nanomedicine. Herein, we aim to review various drug carrier systems and release systems specifically targeting pediatric lung diseases. The injection of nanomedicine into in vivo models and their elimination will also be discussed. Finally, the potential toxicity of nanomaterials will be addressed.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.022
GPT teacher head0.309
Teacher spread0.287 · 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 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

Citations11
Published2013
Admission routes1
Has abstractyes

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