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Record W4323045457 · doi:10.32388/c61u3d

Review of: "The Nexus between Energy Policies and Supply: A Descriptive Evaluation of Nigeria and UK Energy Sectors"

2023· peer-review· en· W4323045457 on OpenAlexaff
Carole Brunet

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsNexus (standard)Energy (signal processing)Descriptive statisticsDescriptive researchBusinessNatural resource economicsEnergy sectorEnvironmental economicsAgricultural economicsEconomicsComputer scienceStatisticsSocial scienceSociologyMathematics

Abstract

fetched live from OpenAlex

Potential competing interests: No potential competing interests to declare.Overall, your article is interesting.Nevertheless, to improve it, I suggest the following 5 points.1/The introduction gives an overview of the energy situation in Nigeria, the issues involved, and the main purpose of the paper.This is a good start.Nevertheless, the reader would have liked to know what the point of such a comparison is.Yes, the UK is the former coloniser of Nigeria, and one can understand this comparison.But why should Nigeria have

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)0.010
metaresearch head score (Gemma)0.107
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: Other · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.107
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.006
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.003

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 head0.051
GPT teacher head0.292
Teacher spread0.241 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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