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Record W2146863600 · doi:10.1614/ws-03-073r

Effects of three herbicides on whole-plant carbon fixation and water use by yellow nutsedge (<i>Cyperus esculentus</i>)

2004· article· en· W2146863600 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWeed Science · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicTurfgrass Adaptation and Management
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMesotrioneCyperusAgronomyHorticultureCarbon fixationWeed controlAssimilation (phonology)ChemistryPhotosynthesisBiologyAtrazineBotanyPesticide

Abstract

fetched live from OpenAlex

Three herbicides were compared for their ability to reduce both carbon fixation and soil water depletion by yellow nutsedge in a growth chamber study. Whole-plant CO 2 exchange and water use were measured for 11 d after herbicide application. MSMA reduced carbon assimilation relative to the untreated control 1 d after treatment, and by 5 d after treatment respiration exceeded carbon assimilation during the photoperiod; however, MSMA had no significant effect on whole-plant water use during the measurement period. Halosulfuron reduced gross carbon assimilation to 30% of the pretreatment rate by the end of the experiment, but in contrast to MSMA it also strongly suppressed water use. Mesotrione never reduced carbon assimilation below 59% of the pretreatment rate and had no measurable effect on water use. Halosulfuron and MSMA reduced shoot regrowth to between 0 and 5% of the control, whereas mesotrione treatment allowed some 58% regrowth. These results indicate that whereas both MSMA and halosulfuron should provide effective control of yellow nutsedge, halosulfuron may be better able to rapidly suppress the weed's ability to compete for available soil water.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score0.704

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 head0.183
Teacher spread0.176 · 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