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Record W4391613178 · doi:10.1002/adfm.202470033

Cucurbit[7]uril‐Mediated Organ‐Specific Delivery of Ultrasmall NIR‐II Luminescent Gold Nanocarriers for Therapy of Acute Kidney Injury (Adv. Funct. Mater. 6/2024)

2024· article· en· W4391613178 on OpenAlexaff
Kui He, Yuan‐Fu Ding, Zhipeng Zhao, Ben Liu, Wenyan Nie, Xiaoxi Luo, Hua‐Zhong Yu, Jinbin Liu, Ruibing Wang

Bibliographic record

VenueAdvanced Functional Materials · 2024
Typearticle
Languageen
FieldMaterials Science
TopicNanocluster Synthesis and Applications
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMaterials scienceNanocarriersNanotechnologyLuminescenceAcute kidney injuryDrug deliveryMedicineOptoelectronicsInternal medicine

Abstract

fetched live from OpenAlex

Kidney-Specific Delivery In article number 2309949, Jinbin Liu, Ruibing Wang, and co-workers develop a series of ultrasmall NIR-II emitting gold nanocarriers, allowing for fine-tuning liver or kidney-specific delivery via altering the surface chemistry using cucurbit[7]uril and Cys-Arg-Gly-Asp peptide. Accordingly, the selected ultrasmall nanocarriers could facilitate kidney-targeted delivery in acute kidney injury mice, which significantly boosts drug accumulation at the site of injured kidneys, thereby achieving improved therapeutic results.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0040.000

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 head0.014
GPT teacher head0.242
Teacher spread0.228 · 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.

Study designBench or experimental
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

Citations1
Published2024
Admission routes1
Has abstractyes

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