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Record W3193196878 · doi:10.53390/ijes.v11i2.1

GROWTH, FLOWERING AND FRUITING PERFORMANCE OF COFFEE (COFFEA ROBUSTA) AS INFLUENCED BY ORGANIC-BASED FORTIFIED FOLIAR FERTILIZER

2020· article· en· W3193196878 on OpenAlexaff
Alminda Magbalot‐Fernandez, Daisy Fernandez, Saikat Basu

Bibliographic record

VenueInternational Journal on Environmental Sciences · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLeaf Properties and Growth Measurement
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsRandomized block designFertilizerMathematicsHorticultureOrganic fertilizerForensic scienceNon-invasive ventilationBiologyToxicologyAgronomyMedicineVeterinary medicine

Abstract

fetched live from OpenAlex

The study was conducted to determine the effect of Greenshield Organic-Based Fortified Foliar Fertilizer on the growth, flowering and fruiting performance of Coffea robusta. The experiment was laid out using Randomized Complete Block Design (RCBD), having six treatments and three replications. The treatments were: T1 – Untreated check (No fertilizer); T2 – RR of NPK fertilizer/ha; T3 – ½ RR NPK/ha; T4 – Greenshield Organic – Based Fortified Foliar Fertilizer at 100ml/li of water; T5 – ½ RR NPK + GOFF; and T6 – RR of NPK + GOFF. The result of the study revealed that different rates of Greenshield Organic – Based Fortified Foliar Fertilizer significantly affected the number of flowers and number of fruits, but not stem diameter. Results showed that the number of flowers at 30 Days after application was increased by T6 – RR of NPK + GOFF up to 36% higher than without applications. It also had the highest number of fruits in two weeks from flowering as much as 100% more fruits than GOFF alone and untreated. While no significant increase in terms of stem diameter was observed which ranged from 75 to 90 cm at 30 days after application.

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 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.707

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)0.0010.000

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 head0.024
GPT teacher head0.206
Teacher spread0.182 · 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 teacher head, 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

Citations0
Published2020
Admission routes1
Has abstractyes

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