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Towards the review of the European Union Water Framework Directive: Recommendations for more efficient assessment and management of chemical contamination in European surface water resources

2016· article· en· W2544886233 on OpenAlexaff
Werner Brack, Valeria Dulio, Marlene Ågerstrand, Ian Allan, Rolf Altenburger, Markus Brinkmann, Dirk Bunke, Robert M. Burgess, Ian T. Cousins, Beate I. Escher, Félix Hernández, L. Mark Hewitt, Klára Hilscherová, Juliane Hollender, Henner Hollert, Robert Kaše, Bernd Klauer, C. Lindim, David López Herráez, Cécile Miège, John Munthe, Simon O’Toole, Leo Posthuma, Heinz Rüdel, Ralf B. Schäfer, Manfred Sengl, Foppe Smedes, Dik van de Meent, Paul J. Van den Brink, Jos van Gils, Annemarie P. van Wezel, A. Dick Vethaak, Etiënne L.M. Vermeirssen, Peter C. von der Ohe, Branislav Vrana

Bibliographic record

VenueThe Science of The Total Environment · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Science and Water Management
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsWater Framework DirectiveEuropean unionDirectiveContaminationWater contaminationSurface waterWater resourcesEnvironmental scienceEnvironmental planningBusinessEnvironmental resource managementEnvironmental protectionWater resource managementWater qualityEnvironmental engineeringComputer scienceInternational tradeBiology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.061
metaresearch head score (Gemma)0.076
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: Review · Consensus signal: Review
Teacher disagreement score0.061
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0610.076
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0100.010
Science and technology studies0.0020.004
Scholarly communication0.0110.008
Open science0.0060.004
Research integrity0.0140.009
Insufficient payload (model declined to judge)0.0030.002

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 head0.011
GPT teacher head0.244
Teacher spread0.232 · 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
GenreReview

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

Citations358
Published2016
Admission routes1
Has abstractno

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