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Record W4411475706 · doi:10.5539/jsd.v18n4p97

Qualities of Colubrina Glandulosa Perkins Seedlings Produced in TNT Containers and Water-Retaining Polymer

2025· article· en· W4411475706 on OpenAlexvenueno aff
Jacyelli Sgranci Angelos, Carlos Henrique Rodrigues de Oliveira, Marcos Vinícius Winckler Caldeira, Fabrícia Benda de Oliveira, Lorayne Saluci Ramos

Bibliographic record

VenueJournal of Sustainable Development · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGrowth and nutrition in plants
Canadian institutionsnot available
FundersUniversidade Federal do Espírito SantoFundação de Amparo à Pesquisa e Inovação do Espírito Santo
KeywordsSeedlingGreenhouseHorticultureTukey's range testPlastic bagEnvironmental sciencePulp and paper industryMaterials scienceBiologyComposite materialEngineering

Abstract

fetched live from OpenAlex

Given the relevance of studies focusing on the production of native forest seedlings and biodegradable containers and the use of new inputs to increase seedling survival in the field, the aim of this work was to evaluate the effect of TNT bags and hydroretentive polymer on the production of Sobrasil seedlings. The experiment occurred in the greenhouse, at the Federal Institute of Espírito Santo, Alegre campus. Six treatments were evaluated, differing between container and addition or not of hydrogel, evaluating morphological and physiological parameters. The data were processed by analysis of variance at 5% significance, and when they showed significant differences, they were compared using the Tukey test at 5% probability. The results demonstrate that the seedlings produced in TNT bags with and without holes had qualities equal to those in plastic bags. The use of hydrogel was only beneficial when combined with a TNT bag without holes.

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 score0.002
Threshold uncertainty score0.004

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 integrity0.0000.001
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 head0.010
GPT teacher head0.212
Teacher spread0.203 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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