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Record W2792803517 · doi:10.5539/jas.v10n4p409

Yield of the Okra Submitted to Nitrogen Rates and Wastewater in Northeast Brazilian Semiarid Region

2018· article· en· W2792803517 on OpenAlex
Aldair de Souza Medeiros, Manoel Moisés Ferreira de Queiroz, Renato Américo de Araújo Neto, Patrícia da Silva Costa, Amanda Costa Campos, Ivomberg Dourado Magalhães, Sebastião de Oliveira Maia Júnior, Luan Danilo Ferreira de Andrade Melo, Giordano Bruno Medeiros Gonzaga

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsnot available
Fundersnot available
KeywordsIrrigationWastewaterContext (archaeology)Randomized block designEnvironmental scienceNitrogenAgronomyYield (engineering)GeographyEnvironmental engineeringBiologyChemistry

Abstract

fetched live from OpenAlex

Water is an indispensable resource for the maintenance of life; however, the available volume for consumption has decreased over a period of life, as a result of which, the availability of water that is inferior in quality has increased. In this context, we aimed to evaluate the growth and yield of okra (Santa Cruz cultivar) under different nitrogen rates and irrigation facilities using post-treated domestic wastewater through sand filter with intermittent flow in a Brazilian semiarid region. The experiment was performed in the Pombal region of the Paraíba state, Brazil using a randomized block design with six nitrogen Rates (N1 = 0, N2 = 40, N3 = 80, N4 = 120, N5 = 160, and N6 = 200 kg ha-1) and irrigation by using wastewater. The water was added to the treatment with 100% (160 kg ha-1) using nitrogen fertilization recommendation and irrigation water supply. The effects of treatments on the growth and production variables of okra plants were evaluated.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score0.148

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.017
GPT teacher head0.226
Teacher spread0.209 · 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