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Nitrate reduction in geologically heterogeneous catchments — A framework for assessing the scale of predictive capability of hydrological models

2013· article· en· W2157812301 on OpenAlexaff
Jens Christian Refsgaard, Esben Auken, Charlotte A. Bamberg, B. S. Christensen, Thomas Clausen, E. Dalgaard, Flemming Effersø, Vibeke Ernstsen, Flemming Gertz, Anne Lausten Hansen, Xin He, Brian H. Jacobsen, Karsten H. Jensen, Flemming Jørgensen, Lisbeth Flindt Jørgensen, Julian Koch, Bertel Nilsson, Christian E. Petersen, Guillaume De Schepper, Cyril Schamper, Kurt Sørensen, René Therrien, Christian Thirup, Andrea Viezzoli

Bibliographic record

VenueThe Science of The Total Environment · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsScale (ratio)Environmental scienceNitrateReduction (mathematics)Hydrology (agriculture)Earth scienceSoil scienceGeologyGeographyEcologyMathematicsCartographyGeotechnical engineeringBiology

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 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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score0.997

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 studies0.0000.006
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.015
GPT teacher head0.237
Teacher spread0.221 · 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 designSimulation or modeling
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

Citations93
Published2013
Admission routes1
Has abstractno

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