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Record W4377821759 · doi:10.22214/ijraset.2023.52539

Social Sphere: A MERN Stack Social Media App

2023· article· en· W4377821759 on OpenAlexfundno aff
Asif Malik

Bibliographic record

VenueInternational Journal for Research in Applied Science and Engineering Technology · 2023
Typearticle
Languageen
FieldComputer Science
TopicMobile and Web Applications
Canadian institutionsnot available
FundersMinistère de l'Énergie et des Ressources Naturelles
KeywordsJavaScriptComputer scienceWorld Wide WebPerlJavaOperating systemStack (abstract data type)Call stackWeb applicationLeverage (statistics)The Internet

Abstract

fetched live from OpenAlex

Abstract: In today's ever-evolving tech industry, there is a significant surge in the demand for full-stack developers. Reports suggest that skilled professionals in this field, particularly in the United States, can expect remarkable average profits, with figures reaching as high as $110,770, according to Real. A full-stack developer is an individual who possesses the technical expertise to handle both the front-end and back-end aspects of dynamic websites and internet-based applications. Web development often revolves around frameworks like the LAMP stack (Linux, Apache, MySQL, PHP/Perl) and Java (Java EE, Spring), which incorporate a combination of programming languages. Additionally, JavaScript plays a crucial role in enhancing web experiences, enabling developers to leverage the MERN stack (MongoDB, Express.js, React.js, and Node.js). This comprehensive technology stack empowers developers to effectively address user interface requirements and server-side operations

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0250.010

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 head0.078
GPT teacher head0.402
Teacher spread0.324 · 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 designNot applicable
Domainnot available
GenreSoftware

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

Citations1
Published2023
Admission routes1
Has abstractyes

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