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Record W2300761993

Improved growth, seed yield and quality of fennel (Foeniculum vulgare Mill.) through soil applied nitrogen and phosphorus.

2015· article· en· W2300761993 on OpenAlexaff
Muhammad Ashar Ayub, Rizwan Maqbool, Muhammad Usman Tahir, Zoaib Aslam, Muhammad Nadeem, Muhammad Ibrahim

Bibliographic record

VenuePakistan Journal of Agricultural Research · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Science and Fertilization
Canadian institutionsDalhousie University
Fundersnot available
KeywordsFoeniculumPhosphorusFertilizerAgronomyYield (engineering)NitrogenChemistryField experimentHorticultureMathematicsBiology
DOInot available

Abstract

fetched live from OpenAlex

In Pakistan, fennel is conventionally grown without fertilizer. A field experiment, was conducted to study the effects of nitrogen and phosphorus fertilizer treatments (NP in ratio of 0:0, 30:0, -1 0:30, 30:15, 30:30, 60:30, 60:60, 90:45 and 90:90 kg ha ) on growth, seed yield and quality of fennel during 2011-2012. Fertilizer NP dose (90:45 kg -1 ha ) increased plant height by 44%, number of leaves per plant by 76%, 1000 seed weight by 44%, biological yield by 50%, seed yield by 296%, harvest index by 162% and protein content by 6%. However, fertilizer NP -1 (90:45 kg ha ) decreased oil content by 26%. Therefore, addition of NP fertilizer had the potential to increase fennel seed yield, but reduce oil content, under Faisalabad conditions.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.110
GPT teacher head0.334
Teacher spread0.224 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2015
Admission routes1
Has abstractyes

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