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Record W7065487517

ECA Office for North Africa pursues programme implementation despite COVID19

2020· other· en· W7065487517 on OpenAlexaboutno aff

Bibliographic record

VenueEconomic Commission for Africa Knowledge Repository (Economic Commission for Africa) · 2020
Typeother
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsAccountabilityQuarter (Canadian coin)Coronavirus disease 2019 (COVID-19)Focus (optics)Event (particle physics)Front linePandemic
DOInot available

Abstract

fetched live from OpenAlex

Despite the impact of COVID19 on event organization and technical support missions to member countries, ECA’s Office for North Africa has met half of its targeted results for 2020 so far. This achievement was acknowledged at ECA’s Second Quarter Accountability and Programme Performance Review Meeting (APPR). Participants however acknowledged that the pandemic’s negative impact on stability across North Africa may generate obstacles to the office’s upcoming work, forcing it to postpone activities requiring the physical presence of stakeholders until the situation improves and to focus instead on the organization of virtual meetings and webinars whenever possible.

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)0.025
metaresearch head score (Gemma)0.034
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: Other
Teacher disagreement score0.072
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.034
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0090.005
Open science0.0020.008
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0720.017

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 head0.044
GPT teacher head0.292
Teacher spread0.248 · 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
Published2020
Admission routes1
Has abstractyes

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