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Record W2188600042 · doi:10.21273/hortsci.37.1.95

Response of Plasticultured Bell Pepper to Staking, Irrigation Frequency, and Fertigated Nitrogen Rate

2002· article· en· W2188600042 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueHortScience · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsnot available
FundersAgriculture and Agri-Food Canada
KeywordsFertigationIrrigationMulchDry matterDrip irrigationPepperYield (engineering)HorticultureAgronomyWater contentNitrogenEnvironmental scienceBiologyChemistryMaterials science

Abstract

fetched live from OpenAlex

Effects of staking, drip irrigation frequency and fertigated N rate on dry matter partitioning and yield of bell peppers ( Capsicum annuum L.), grown using polyethylene mulch and mini-tunnels, were determined in two years. In the second year, which had higher early-season temperatures and more hours of direct sunlight, plants were larger, more productive and had larger fruit with thicker pericarps and a higher water content than in the first year. In both years, staked plants fertigated with 31.5 vs. 63 kg·ha -1 N produced higher yields due to increased fruit size and pericarp thickness. Compared with the response to monthly irrigation plus rainfall, additional irrigation applied when the soil moisture tension averaged below -25 and -20 kPa in the two years, respectively, affected yield only in the second year when it increased yield and the number of fruits produced by staked plants and decreased that of non-staked plants. Patterns of vegetative development and dry matter partitioning indicate that resources were remobilized from leaves to support fruit development.

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)0.001
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 score0.896
Threshold uncertainty score0.432

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.026
GPT teacher head0.215
Teacher spread0.189 · 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