MétaCan
Menu
Back to cohort
Record W3192802989 · doi:10.3390/nano11082008

Stand-Alone CuFeSe2 (Eskebornite) Nanosheets for Photothermal Cancer Therapy

2021· article· en· W3192802989 on OpenAlexaff
Mimi Liu, Daniela R. Radu, Gurpreet Singh Selopal, Saiphaneendra Bachu, Cheng‐Yu Lai

Bibliographic record

VenueNanomaterials · 2021
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsInstitut National de la Recherche Scientifique
FundersSLAC National Accelerator LaboratoryDivision of Chemical, Bioengineering, Environmental, and Transport SystemsNational Science Foundation of Sri LankaNuclear Safety and Security CommissionDivision of Materials ResearchNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsPhotothermal therapyBiocompatibilityMaterials scienceTransmission electron microscopyDoxorubicinIrradiationNanotechnologyPhotothermal effectLaserOpticsMedicineChemotherapy

Abstract

fetched live from OpenAlex

Two-dimensional CuFeSe2 nanosheets have been successfully obtained via solution-phase synthesis using a sacrificial template method. The high purity was confirmed by X-ray diffraction and the two-dimensional morphology was validated by transmission electron microscopy. The intense absorption in the 400–1400 nm region has been the basis for the CuFeSe2 nanosheets’ photothermal capabilities testing. The colloidal CuFeSe2 (CFS) nanosheets capped with S2− short ligands (CFS-S) exhibit excellent biocompatibility in cell culture studies and strong photothermal effects upon 808 nm laser irradiation. The nanosheets were further loaded with the cancer drug doxorubicin and exposed to laser irradiation, which accelerated the release of doxorubicin, achieving synergy in the therapeutic effect.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.123
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0160.000

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 head0.049
GPT teacher head0.297
Teacher spread0.248 · 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

Citations17
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueNanomaterialsSame topicQuantum Dots Synthesis And PropertiesFrench-language works237,207