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Record W4302012001 · doi:10.32920/ryerson.14657208

Aluminum Based Nanosensors for Ultrasensitive Bio-Detection

2022· preprint· en· W4302012001 on OpenAlexaff
Sri Sankari Ganesan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRhodamine 6GNanosensorMaterials scienceNanomaterialsNanotechnologyNanoprobeFemtosecondRaman spectroscopyLaserCancer cellCrystal violetChemistryCancerMoleculeNanoparticleOptics

Abstract

fetched live from OpenAlex

A 3-dimensional, biocompatible Aluminum based nanomaterial with tunable morphological properties is fabricated using Femtosecond Pulsed Laser system. The novel material synthesized is characterized to define its physical and optical properties owing to its purpose in the desired field. Two unique shapes of Aluminum nanostructures, multifaceted and spherical, are defined and tested for Raman activity in SERS based applications. The nanoprobes are analysed in the field of chemical sensing using Crystal Violet and Rhodamine 6G and bio-sensing using cysteine and carcinoembryonic antigen. The nanoprobes possess the ability of SERS excitation up to single molecule sensing. The research is extended to in-vitro cancer diagnosis by its ability to sense the intracellular biomarkers produced by the cancer cells. Three cell lines are evaluated, mammalian fibroblast and pancreatic and lung cancer cells, for which further analysis is performed to prove the viability of the nanoprobes to differentiate between cancerous and non-cancerous cells by implementing ratio analysis on the obtained SERS spectrum

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.262
Teacher spread0.237 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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