MétaCan
Menu
Back to cohort
Record W1873751326 · doi:10.21273/horttech.16.4.0583

Rotary Hoe Cultivation in Sweet Corn

2006· article· en· W1873751326 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

VenueHortTechnology · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsSte. Anne's HospitalMcGill UniversityInstitut de Recherche et de Développement en Agroenvironnement
Fundersnot available
KeywordsSowingAgronomyCultivarWeedCropWeed controlYield (engineering)Zea maysBiologyHorticultureMathematics

Abstract

fetched live from OpenAlex

A 2-year study was conducted to assess sweet corn ( Zea mays ) susceptibility to mechanical weeding using a rotary hoe at preemergence to six-leaf stages of corn development and at different combinations of stages. Three sweet corn cultivars: early (`Quickie'), mid (`July Gem'), and late season (`Sensor') were seeded at two sowing dates. The experiment was conducted in a weed-free environment. In general, sweet corn could be cultivated with the rotary hoe at least once without yield reduction from preemergence to the six-leaf stage. Cob numbers were reduced and maturity delayed after three or four cultivations with the rotary hoe. The rotary hoe could be an effective tool in controlling weeds in an integrated weed management approach or for organic sweet corn production since it cultivates both within and between the rows. The rotary hoe, which covers a large area in a short time, can be used at later growth stages, extending the time period during which it can be used without damaging the crop and reducing yield.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.964

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 head0.008
GPT teacher head0.195
Teacher spread0.187 · 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