MétaCan
Menu
Back to cohort
Record W2182728288

Towards a Regional Strategy for the Management of the Transboundary Aquifer Systems in the Americas

2010· article· en· W2182728288 on OpenAlexaboutno aff
Alfonso Rivera, Alyssa Dausman, N. DaFranca, Julio T.S. Kettelhut, William M. Alley, Rubén Chávez-Guillén, Maria Prieto-Espinoza, Límites del Estado, Ciencias Hídricas

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicInternational Maritime Law Issues
Canadian institutionsnot available
Fundersnot available
KeywordsAquiferPolitical scienceResource (disambiguation)GeographyEnvironmental planningEnvironmental resource managementEnvironmental protectionEngineeringEnvironmental scienceGroundwater
DOInot available

Abstract

fetched live from OpenAlex

The Internationally Shared Aquifer Resource Management (ISARM)-Americas initiative has been successful in promoting cooperation in the sharing of data and information on transboundary aquifer systems (TAS) amid 24 countries from Argentina to Canada. Over a period of seven years (2003-2009), the ISARM-Americas initiative, jointly sponsored and coordinated by United Nations Educational, Scientific and Cultural Organization (UNESCO) and the Organization of American States (OAS), succeeded in inventorying 73 TAS in the American hemisphere. The initiative has produced two books; one containing the inventory of the 73 TAS in 2007, and a second one describing the legal and institutional aspects of the 73 TAS, in 2008. A third book is in preparation with a synthesis of the socio-economic, environmental and climatic aspects of the 73 TAS. The ISARM-Americas group is now preparing a regional strategy for the management of the transboundary aquifer systems in the American hemisphere. The regional strategy will be published as a fourth book in 2010 with a synthesis of the socio-economic, environmental and climatic aspects of the 73 TAS. This paper summarizes the current activities towards the preparation of the third book.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.937
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.279
Teacher spread0.255 · 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 designTheoretical or conceptual
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
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicInternational Maritime Law IssuesFrench-language works237,207