MétaCan
Menu
Back to cohort
Record W6893042430 · doi:10.5281/zenodo.13847836

A Spatio-Topographical Assessment of Mobile Network Quality in Rocky Terrains: A Case Study of Dutsin-Ma Town

2024· article· en· W6893042430 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Languageen
FieldEngineering
TopicMillimeter-Wave Propagation and Modeling
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTerrainQuality (philosophy)Cellular networkSampling (signal processing)Relation (database)Sample (material)Systematic samplingMobile telephony

Abstract

fetched live from OpenAlex

The Research is aimed at identifying the spatial distribution and variation of mobile phones network quality in the study area which is dominated by irregular topography, inselbergs and rock outcrops. To achieve this aim, fifty (50) sampled areas were selected in Dutsin-Ma Town based on the nature of their rugged terrain and rocky landscape. Smart phones were used to collect Ultra-High Frequency (UHF) data using systematic grid sampling technique to determine the network strength of MTN, GLOBACOM, AIRTEL, and ETISALAT. A total of one hundred (100) structured questionnaires were also distributed to residents to obtain the necessary information to validate the results from users’ perspective. The research found out that generally Dutsin-Ma is a not a town with good network as average (48%) and poor (36%) network quality dominates the area; only 16% of the areas have good network quality. From the questionnaire survey, majority (43%) of the respondents are using MTN because of its high quality and resistance especially in areas with rock outcrops. It was also found that areas around Motel, Gidan Ruwa, Hayin Gada, all of relatively moderate relief (512-578m) has the best Network; Unguwar Tsamiya, Dan Kauye and Tsohuwar Kasuwa have average Network while areas like Unguwar Alkali and Unguwar Wakaji have poor network quality. It was therefore concluded that network challenges in some areas have (in addition to other factors) a strong connection with elevation, rugged terrain and rocky landscape. However, in some few instances (Kadangaru and Makarantar Gabas), quality of some network like GLO and Airtel increases with altitude. It was also found that rugged terrains constitute a barrier to successful installation of masts in many locations. The research recommended adequate town and landuse planning that will ensure improved spatial distribution of masts for quality phone signals of all networks across Dutsin-Ma area.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.308
Teacher spread0.261 · 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 designObservational
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicMillimeter-Wave Propagation and ModelingFrench-language works237,207