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Record W2056632516 · doi:10.6000/1927-5129.2013.09.68

Remapping Hydroecoregion Boundaries: A Proposal for Improving the Base of the Running Water Monitoring Procedures

2013· article· en· W2056632516 on OpenAlexvenueno aff
Lorenzo Traversetti, Alessandro Manfrin, Massimiliano Scalici

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsThreatened speciesSafeguardScale (ratio)Environmental resource managementHomogeneousWater Framework DirectiveDirectiveEuropean unionOrder (exchange)Habitats DirectiveGeographyComputer scienceEnvironmental planningEnvironmental scienceHabitatCartographyPolitical scienceBusinessEcologyLawWater qualityMathematics

Abstract

fetched live from OpenAlex

Inland waters are constituted by a lot of seriously threatened habitats. The increasing need to safeguard these ecosystems led European Union Member States to propose the Water Framework Directive which decided the creation of homogeneous areas characterized by very similar geology, topography and climate, known as hydroecoregions (HER) and firstly proposed by the French National Research Institute of Science and Technology for Environment and Agriculture (Cemagref). Watercourses reference conditions had to be defined within any HER in order to confront any sampling site. HERs are consistent with European scale maps but important local reinterpretations in order to define more precise boundaries and extensions for each hydroecoregion are required and this point constitutes the main goal of this manuscript.Latium is a climatically very homogeneous region and it’s roughly divided into three major portions confirming Cemagref’s proposal. Geological and topolographical maps were then used in order to achieve a more detailed characterization of this region in order to obtain a more defined map. All our results allow to better define similarities and differences both between streams and within the same stream allowing to entirely locate each water course within the same HER. It would be important to follow up this study by proposing a similar approach for the entire national territory based on an appropriate region knowledge.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.218
Teacher spread0.207 · 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

Citations4
Published2013
Admission routes1
Has abstractyes

Explore more

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