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Record W4399366723 · doi:10.1038/s44221-024-00264-z

Author Correction: Energy trade tempers Nile water conflict

2024· article· en· W4399366723 on OpenAlexaff
Mikiyas Etichia, Mohammed Basheer, Ruben Bravo, José Nicolás Melchor Gutiérrez, Atsede G. Endegnanew, José María Faci González, Anthony Hurford, James Tomlinson, Eduardo A. Martínez, Mathaios Panteli, Julien Harou

Bibliographic record

VenueNature Water · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEnergy (signal processing)Environmental scienceWater resource managementMathematicsStatistics

Abstract

fetched live from OpenAlex

In the version of the article initially published, the source data files for Fig. 2–4 were incorrect and have now been replaced in the HTML version of the article. Additionally, the sentence “All simulated scenarios assume an initial HAD storage volume of 162 bcm following satellite altimetry data sourced from Copernicus Land Surface” has been added to the final paragraph of the “EAPP river basin model” section in the HTML and PDF versions of the article.

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)0.002
metaresearch head score (Gemma)0.038
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 score0.102
Threshold uncertainty score0.340

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.1020.045

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 head0.006
GPT teacher head0.219
Teacher spread0.213 · 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
Published2024
Admission routes1
Has abstractyes

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