MétaCan
Menu
Back to cohort
Record W4385557992 · doi:10.14447/jnmes.v26i2.a06

Synthesis and Characterization of Multi Metal Oxide Nanocomposite (ZnO-SrO-MgO) and Its Applications

2023· article· en· W4385557992 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2023
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Oxide Properties and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsNanocompositeCharacterization (materials science)Materials scienceMetalOxideZincNanotechnologyChemical engineeringMetallurgyEngineering

Abstract

fetched live from OpenAlex

Nanotechnology used widely due its smaller in size and massive application in all field of science.Metal oxide nanoparticles are a significant class of nanomaterials with numerous uses in both science and technology.A heterogeneous, versatile multi metal oxid ZnO-SrO-MgO has been prepared by chemical co-precipitation method.Synthesis can achieve selected surface structure, phase, shape and size of metal oxide nanoparticles, resulting in a set of desired attributes.The synthesized multi metal oxide nanoparticles were characterized by various instrumental techniques.The synthesized multi metal oxide materials beautifully present in nano meter level as 94 nm identified through SEM analysis.Absorption spectra from UV confirmed the multi metal oxide from its corresponding peaks.XRD peaks with plane obtained in the range it's confirmed the presence nanoparticles.Multi metal oxide exhibits good antifungal and antimicrobial activity

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.

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 score0.003
Threshold uncertainty score0.442

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 head0.020
GPT teacher head0.250
Teacher spread0.230 · 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