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Record W7133326063 · doi:10.65521/mjret.v9i1.1149

Women’s Safety System

2022· article· W7133326063 on OpenAlexaff
Nitin Chauhan, Sanket Nirmale, Rachana Parsewar, Ninad Mathapati, Prof. Sheetal Phatangare

Bibliographic record

VenueMultidisciplinary Journal of Research in Engineering and Technology · 2022
Typearticle
Language
FieldEngineering
TopicIoT and GPS-based Vehicle Safety Systems
Canadian institutionsWSP (Canada)
Fundersnot available
KeywordsGlobal Positioning SystemAndroid (operating system)Smart phoneEvent (particle physics)PhoneSecurity systemMobile phoneSystem safety

Abstract

fetched live from OpenAlex

Women's Safety Security System - Alert All Chat Application People using smart phones has grown fast in today's culture, and so a smart phone can be efficiently used for personal security or other types of protection. The horrific event that shocked the entire country has reawakened us to the need of addressing safety problems, and as a result, a plethora of new apps have been developed to provide women with protection systems through their phones. If the necessity arises, this Android App for Women's Safety and Security can be activated with a single click. A single click on this app recognises the location of a location using GPS and sends a message with the location URL to the registered contacts, as well as summoning the first registered contact to assist the person in a perilous situation.

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)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.004
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.006
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 head0.022
GPT teacher head0.286
Teacher spread0.265 · 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.

Study designSimulation or modeling
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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