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IMPACT AND PERSPECTIVES ON WATER SUPPLY AND SANITATION NETWORK

2017· article· en· W3197496033 on OpenAlexaff
Vera Maria Lopes Ponçano, Genesis Duarte de Oliveira SILVA

Bibliographic record

VenuePERIÓDICO TCHÊ QUÍMICA · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Sustainability and Education
Canadian institutionsImpact
Fundersnot available
KeywordsSanitationLinkage (software)BusinessWater supplyKnowledge managementEnvironmental planningComputer scienceEngineeringGeographyEnvironmental engineering

Abstract

fetched live from OpenAlex

The Sanitation and Water Supply Network (RESAG) is under the Brazilian Technology System Network (SIBRATEC) -Technological Services, aiming to improve and extend the technological services offered by the organizations comprised in this network. Planning and education are fundamental for the solution of the existing problems and there are actions not necessarily expensive that can result in a positive and meaningful impact, as the one coming from the approach and linkage of public and private institutions and many technological sectors, involving many discipline of the knowledge. The management in the form of a network, such as RESAG, facilitates permeability and the dissemination of knowledge in this area in the various regions of the country.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.256
Teacher spread0.247 · 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.

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

Citations1
Published2017
Admission routes1
Has abstractyes

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