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Record W2738992540 · doi:10.20286/jeas.v2i1.12

Quantity of Indiscriminately Disposed Sachet Water Wastes Generated in Nsukka Urban, Enugu State, Nigeria

2016· article· en· W2738992540 on OpenAlexvenueno aff
N. D Ezeokpube, Chinwe Joy Obiora

Bibliographic record

VenueNova Journal of Engineering and Applied Sciences · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsDispose patternGovernment (linguistics)BusinessWaste managementWaste disposalEnvironmental planningAgricultural economicsEnvironmental scienceEngineeringEconomics

Abstract

fetched live from OpenAlex

The popularity of sachet water consumption in Nigeria is not without problems with regards to its disposal. The study invested evidence for indiscriminate disposal of sachet water waste and the quantities (kg) of the waste generated in various wards in Nsukka urban. Pictures taken round the various wards show empirical evidences that sachet water waste is indiscriminately disposed in the study area. The study equally shows that Nkpunano ward has the highest (23kg) quantity of indiscriminately disposed sachet water wastes generated in Nsukka urban, followed by Owerre ward (19kg), Ihe ward (18kg), University ward (15kg), Nru ward (9kg) and Government Reserved Area (4kg). The study therefore recommends: (1) the necessity for the proper re-orientation of the people on the need for adequate disposal of sachet water waste (2) the need for authorities concerned providing dumpsters at strategic places so that people can conveniently dispose sachet water wastes. Keywords: Waste, Sachet, Water, Disposal, Indiscriminate, Nsukka

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score0.230

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.042
GPT teacher head0.267
Teacher spread0.225 · 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 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

Citations1
Published2016
Admission routes1
Has abstractyes

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