MétaCan
Menu
Back to cohort
Record W2039123226 · doi:10.1614/ws-07-201.1

Interactions of ALS-Inhibiting Herbicide Residues in Three Prairie Soils

2008· article· en· W2039123226 on OpenAlexafffundabout
Bryce G. L. Geisel, J.J. Schoenau, F.A. Holm, Eric N. Johnson

Bibliographic record

VenueWeed Science · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicPesticide and Herbicide Environmental Studies
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Saskatchewan
FundersSaskatchewan Pulse Growers
KeywordsBioassayAcetolactate synthaseResidue (chemistry)ChemistryPhytotoxicitySoil waterPesticideAgronomyEnvironmental chemistryBiologyEcologyBiochemistry

Abstract

fetched live from OpenAlex

The objective of this study was to determine if the presence of two acetolactate synthase (ALS)-inhibiting herbicide residues in different Saskatchewan soils would result in additive, synergistic, or antagonistic interactions. This was determined through field trials where herbicides were applied sequentially over the course of 2 yr. The herbicides examined in these experiments were imazamethabenz, flucarbazone, sulfosulfuron, and florasulam, each in combination with imazamox and imazethapyr. The phytotoxicity and persistence of the herbicides in soil was assessed using an oriental mustard root inhibition bioassay. The determination of herbicide interaction was made through the comparison of the experimentally observed values to theoretically expected values derived from a mathematical equation. On the basis of the bioassay analysis, it was found that the herbicide residue combinations resulting from sequentially applied ALS-inhibiting herbicides in the three soils produced additive injury effects rather than synergistic or antagonistic interactions.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
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 head0.028
GPT teacher head0.262
Teacher spread0.235 · 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

Citations10
Published2008
Admission routes3
Has abstractyes

Explore more

Same venueWeed ScienceSame topicPesticide and Herbicide Environmental StudiesFrench-language works237,207