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OPTIMUM NITROGEN FERTILIZATION OF SUMMER CABBAGE IN ONTARIO

2003· article· en· W2589645777 on OpenAlex
Sean M. Westerveld, Mary Ruth McDonald, A.W. McKeown, Cynthia Scott‐Dupree

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

VenueActa Horticulturae · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHuman fertilizationNitrogen fertilizerEnvironmental scienceNitrogenAgronomyBiologyChemistryFertilizer

Abstract

fetched live from OpenAlex

The recent introduction of nutrient management legislation in Ontario may force vegetable growers to reduce nitrogen (N) application. Experiments were conducted on mineral soil in Simcoe, Ontario in 2000 and 2001 to re-evaluate the N needs of cabbage. Nitrogen application rates of 0, 85, 170, 255, and 340 kg ha-1 were applied 75% preplant and 25% sidedress to Atlantis, a mid-season cultivar. Total yield,
\nmarketable yield, weight per head, head density, and head size were assessed at harvest. In 2001, total yield showed a peak at 265 kg N ha-1 while in 2001 no significant effect was recorded. Head size and weight per head increased with increasing N rate only in 2000, reflecting differences in yield. Cabbage density was generally unaffected by N rate. Days to maturity decreased with increasing N rate reaching a minimum at 245 and 226 kg ha-1 in 2000 and 2001, respectively. Nitrogen rates above current recommended levels are beneficial in maximizing cabbage yields in wet years and minimizing days to maturity.

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 score0.643
Threshold uncertainty score0.919

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 head0.034
GPT teacher head0.218
Teacher spread0.184 · 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