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Record W1981791785 · doi:10.1614/wt-03-156r1

Sweet Corn Cultivar Sensitivity to Bentazon

2004· article· en· W1981791785 on OpenAlex
Shane Diebold, Darren E. Robinson, J.W. Zandstra, John O’Sullivan, Peter H. Sikkema

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 · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBentazonCultivarWeed scienceAgronomyHorticultureBiologyWeed control

Abstract

fetched live from OpenAlex

Five sweet corn cultivars were evaluated for tolerance to bentazon in five field experiments conducted during 2 yr in Ontario. Bentazon was applied postemergence (POST) at 1.08 and 2.16 kg ai/ha, the highest registered rate and twice the highest registered rate, respectively, used in sweet corn in Ontario. When bentazon was applied POST at 1.08 and 2.16 kg/ha to sweet corn cultivar ‘DelMonte 2038’, injury included plant stunting and leaf damage ranging from 6 to 69% and 15 to 90%, respectively. Plant height was reduced to 48 and 100% of the untreated check when treated with bentazon at 1.08 and 2.16 kg/ha, respectively. The visual injury and height reductions were reflected in the marketable yields, which were reduced to 94% when treated with bentazon. Significant reductions in height and marketable yield were not observed in the other four cultivars tested. No correlation was observed between bentazon sensitivity and endosperm genotype. Based on visual injury ratings, sweet corn height, and marketable yield, it was concluded that ‘Calico Belle’, ‘GH 2684’, ‘Reveille’, and ‘Rival’ are tolerant to POST application of bentazon.

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 score0.763
Threshold uncertainty score0.752

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)0.0000.001

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 head0.010
GPT teacher head0.218
Teacher spread0.208 · 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