MétaCan
Menu
Back to cohort
Record W7064378363

Blue economy in North Africa: sectorial analysis for maritime transport.

2019· other· en· W7064378363 on OpenAlexaboutno aff

Bibliographic record

VenueEconomic Commission for Africa Knowledge Repository (Economic Commission for Africa) · 2019
Typeother
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsnot available
Fundersnot available
KeywordsGlobal warmingProduction (economics)Climate changeGreenhouse gasQuarter (Canadian coin)Carbon dioxideLow-carbon economy
DOInot available

Abstract

fetched live from OpenAlex

This document explores the Blue Economy (BE), which integrates the economic utilization of water resources—such as oceans, seas, rivers, lakes, and other water bodies—with strategies to protect their health. Covering over 80% of Earth’s surface, these water bodies are vital life resources. They contribute to half of the global oxygen production and serve as the largest carbon sink, absorbing nearly a quarter of the carbon dioxide emissions. This absorption helps mitigate global warming by sequestering 90% of the additional heat generated by the greenhouse effect.

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)0.003
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 score0.131
Threshold uncertainty score0.261

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.011
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0190.002

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 head0.021
GPT teacher head0.240
Teacher spread0.219 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueEconomic Commission for Africa Knowledge Repository (Economic Commission for Africa)Same topicAstrophysical Phenomena and ObservationsFrench-language works237,207