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Record W2892366450 · doi:10.5539/jas.v10n10p282

Population Arrangement of Crambe Plants

2018· article· en· W2892366450 on OpenAlexvenueno aff
Tiago Roque Benetoli da Silva, Beatriz Tomé Gouveia, Ana Cláudia Mascarello, Affonso Celso Gonçalves-Júnior, Deonir Secco, Charline Zaratim Alves, Reginaldo Ferreira Santos

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGrowth and nutrition in plants
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsCrambeHectareRandomized block designPopulationRaw materialAgronomyBiologyGrain yieldYield (engineering)BiodieselField trialHorticultureMathematicsAgricultureMaterials scienceEcology

Abstract

fetched live from OpenAlex

Crambe (Crambe abyssinica Hochst) is an alternative raw material for biodiesel production. It is highly resistant to drought and has short growing cycle of 90 to 100 days. This work was conducted in Umuarama city, Parana State, Brazil, in Haplortox typical and aimed to study the effect of row spacing and population densities in the development of crambe in two growing seasons. The experimental design was a randomized block in a 3x3 factorial scheme with four replications. The treatments consisted of three row spacing (15, 30 and 45 cm) and three population densities (500 thousand, 750 thousand and 1 million plants per hectare). It was evaluated the thousand grain weight, oil content and grain yield. It can be concluded that high and low spacing plant population lead to smaller yields.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.231
Teacher spread0.213 · 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 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
Published2018
Admission routes1
Has abstractyes

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