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Record W2972970534 · doi:10.5539/jas.v11n16p61

Analysis of Litterfall Biofertilizer and Basalto Powder in Zea mays Culture

2019· article· en· W2972970534 on OpenAlexvenueno aff
Ana Luiza Wnuk, Cláudio Yuji Tsutsumi, Tiago Renato Blomker Böes, Ana Flavia Wnuk

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Management and Crop Yield
Canadian institutionsnot available
Fundersnot available
KeywordsSowingBiofertilizerAgronomyZea maysPlant litterCropNutrientChemistryEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

The objective of this work was to evaluate the compound based on litterfall and basalt powder on the corn crop, in a comparison of physical and chemical soil changes, in order to search development based on the knowledge of nature and natural sources that offer the improvement in the growth of plants for the purpose of organic production. The soil applications were made with aqueous solutions—the mixture in % of the compound and the remainder of the water. Four concentrations (25, 50, 75 and 100% for a 500 ml measurement) of the organic compound and control with 500 ml of water was performed. A total of five corn plants were used for each dosage. The planting was done in lines of 5 plants for 5 dosages (5 × 5). The applications occurred in the pre-planting (directly in the soil, before receiving the seeds) and after every five days.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.457
Threshold uncertainty score0.197

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
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 head0.010
GPT teacher head0.216
Teacher spread0.205 · 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 designObservational
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
Published2019
Admission routes1
Has abstractyes

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