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Record W3020077917 · doi:10.1021/acscentsci.0c00303

X-ray-Activatable Photodynamic Nanoconstructs

2020· article· en· W3020077917 on OpenAlexafffundabout
Marta Overchuk, Miffy H. Y. Cheng, Gang Zheng

Bibliographic record

VenueACS Central Science · 2020
Typearticle
Languageen
FieldEngineering
TopicNanoplatforms for cancer theranostics
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsLibrary scienceMedicineComputer science

Abstract

fetched live from OpenAlex

ADVERTISEMENT RETURN TO ISSUEPREVFirst ReactionsNEXTX-ray-Activatable Photodynamic NanoconstructsX-ray induced photodynamic therapy enables chemotherapy-free treatment of deep-tissue cancer with a low dose of X-ray radiation.Marta OverchukMarta OverchukInstitute of Biomaterials and Biomedical Engineering, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, CanadaPrincess Margaret Cancer Centre, University Health Network, 101 College Street, PMCRT 5-354, Toronto, Ontario M5G 1L7, CanadaMore by Marta Overchuk, Miffy H. Y. ChengMiffy H. Y. ChengPrincess Margaret Cancer Centre, University Health Network, 101 College Street, PMCRT 5-354, Toronto, Ontario M5G 1L7, CanadaMore by Miffy H. Y. Cheng, and Gang Zheng​Gang ZhengInstitute of Biomaterials and Biomedical Engineering, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, CanadaPrincess Margaret Cancer Centre, University Health Network, 101 College Street, PMCRT 5-354, Toronto, Ontario M5G 1L7, CanadaDepartment of Medical Biophysics, University of Toronto, 101 College Street, Toronto, Ontario M5G 1L7, CanadaEmail: [email protected]More by Gang Zhenghttp://orcid.org/0000-0002-0705-7398Cite this: ACS Cent. Sci. 2020, 6, 5, 613–615Publication Date (Web):April 24, 2020Publication History Published online24 April 2020Published inissue 27 May 2020https://doi.org/10.1021/acscentsci.0c00303Copyright © 2020 American Chemical SocietyRIGHTS & PERMISSIONSACS AuthorChoiceArticle Views2634Altmetric-Citations9LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (2 MB) Get e-AlertsSUBJECTS:Photosensitization,Radiation,Toxicity,Tumors,X-rays Get e-Alerts

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.101
Threshold uncertainty score0.337

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1010.028

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 head0.009
GPT teacher head0.194
Teacher spread0.186 · 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 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

Citations19
Published2020
Admission routes3
Has abstractyes

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