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Record W2317235176 · doi:10.2489/jswc.65.5.123a

Transport of thifensulfuron-methyl and tribenuron-methyl in runoff

2010· article· en· W2317235176 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of Soil and Water Conservation · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicPesticide and Herbicide Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSulfonylureaSurface runoffEnvironmental sciencePerennial plantWetlandIrrigationHydrology (agriculture)AgronomySurface waterEnvironmental engineeringEcologyBiologyGeology

Abstract

fetched live from OpenAlex

Sulfonylurea herbicides are highly phytotoxic herbicides that are widely used around the world for the pre- and postemergence control of a wide range of annual and perennial grasses and broadleaf weeds. They have been detected in reservoirs and wetlands in the North American Great Plains with reported detection frequencies of 35% to 52%. Although the source of contamination is not known, high concentrations of a number of herbicides followed rain-fall-generated runoff, suggesting that surface runoff likely contributed to the herbicide loadings. In order to assess the potential contribution of surface runoff, transport of two sulfonylurea herbicides (thifensulfuron-methyl and tribenuron-methyl) was measured in surface runoff from a flood-irrigated wheat field in the Outlook Irrigation District of Saskatchewan, Canada.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.232

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 science0.0000.000
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 head0.007
GPT teacher head0.198
Teacher spread0.192 · 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 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
Published2010
Admission routes1
Has abstractyes

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