MétaCan
Menu
Back to cohort
Record W4402320573 · doi:10.1039/d4nr00581c

Hydrothermal synthesis of metal nanoparticles@hydrogels and statistical evaluation of reaction conditions’ effects on nanoparticle morphologies

2024· article· en· W4402320573 on OpenAlexafffund
Olivier Gazil, D. Alonso Cerrón-Infantes, Nick Virgilio, Miriam M. Unterlass

Bibliographic record

VenueNanoscale · 2024
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaUniversität KonstanzFonds de recherche du Québec – Nature et technologiesUniversité de MontréalCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaAustrian Science Fund
KeywordsSelf-healing hydrogelsNanoparticleHydrothermal circulationMaterials scienceMetalSalt (chemistry)Chemical engineeringHydrothermal synthesisNanotechnologyHydrothermal reactionChemistryPolymer chemistryOrganic chemistryMetallurgy

Abstract

fetched live from OpenAlex

We report a hydrothermal one-pot approach using polysaccharides and salt precursors to synthesize and selectively localize metal nanoparticles in hydrogels, leveraging multivariate regression fits to further evaluate synthesis parameter effects.

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 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: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.024
GPT teacher head0.291
Teacher spread0.267 · 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 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

Citations16
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueNanoscaleSame topicGold and Silver Nanoparticles Synthesis and ApplicationsFrench-language works237,207