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Record W2759771364

Nanotechnology Applications: an Analytic Comparison

2017· article· en· W2759771364 on OpenAlexaff
Abdulrahman Alkandari, Zainab Almesri, Samer Moein

Bibliographic record

VenueJournal of Advanced Computer Science and Technology · 2017
Typearticle
Languageen
FieldEngineering
TopicNanotechnology research and applications
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsNanotechnologyCarbon nanotubeComputer scienceApplications of nanotechnologyEngineeringMaterials science
DOInot available

Abstract

fetched live from OpenAlex

It is very important to consider the fast development of nanotechnology when it comes to real life applications. Creating something tiny with special properties designed to fasten up duration time to accomplish any goal with high accuracy is what nanotechnology all about. During time, there were lot of studies on nanotechnology in general and its applications in many fields. The main purpose of this paper survey is to identify the scientific definitions of nanotechnology, historical background, benefits, approaches, and more specifically studying a Nano particle named Nano Carbon Tube (CNT). CNT is highly used in nanotechnology applications as Central Processing Unit (CPU) cooling system, data storage devices (memory), and sensors. This study will also cover usage of nanotechnology in wireless signals named 5G and toxicity of Nano materials, which is too important to ensure humans and environment safety. Studies showed various results on the impact of CNTs on general health. Some studies showed signs of lung disease and others showed no toxicity. Future research and more detailed experiments should be made to make a closure in the case of CNT materials toxicity.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.903
Threshold uncertainty score0.632

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.012
GPT teacher head0.306
Teacher spread0.294 · 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 designOther design
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
Published2017
Admission routes1
Has abstractyes

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