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Record W2174846894 · doi:10.1614/wt-04-146r1

Responses of Dry Beans to Flumioxazin

2005· article· en· W2174846894 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueWeed Technology · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCultivarDry beanCropHorticultureBiologyShootWhite (mutation)AgronomyDry weight

Abstract

fetched live from OpenAlex

There is little information on the sensitivity of dry beans to flumioxazin. Tolerance of eight cultivars of dry beans representing four market classes (black, cranberry, kidney, and white beans) to preplant incorporated (PPI) and preemergence (PRE) applications of flumioxazin at the rate of 52.5, 70, and 140 g ai/ha were studied in three field experiments in Ontario in 2002 and 2003. There were no differences (P < 0.05) between two cultivars within a market class in their responses to flumioxazin. However, the four market classes differed in their responses to flumioxazin. Black and white beans were more sensitive to the PRE application of flumioxazin than cranberry and kidney beans. Flumioxazin applied PRE at 140 g/ha caused as much as 34% visual injury and reduced plant height by 23 to 28%, shoot dry weight by 35 to 39%, and yield by 20 to 30% in black and white bean market classes. Flumioxazin-applied PPI did not injure any market class. On the basis of this research, there is an acceptable margin of crop safety in these black and white bean cultivars only when flumioxazin is applied PPI. The two cranberry and kidney bean cultivars were tolerant to all rates of flumioxazin applied both PPI and PRE.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score0.291

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 studies0.0000.000
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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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