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Effect of kelp extract on sugarcane plantlets biomass accumulation

2015· article· en· W2267512657 on OpenAlexaff
Luís Cláudio Inácio da Silveira, Pedro Mattos, Átila Francisco Mógor, Edelclaiton Daros, Marcos de Oliveira Bettini, Jeff Norrie

Bibliographic record

VenueIdesia · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPotato Plant Research
Canadian institutionsAcadian Seaplants (Canada)
Fundersnot available
KeywordsAscophyllumBiologyHorticultureBotanyShootBuddingPerennial plantHumanitiesAlgaeArt

Abstract

fetched live from OpenAlex

In order to improve the growth of sugarcane plantlets, this study examined the effects of a seaweed (Ascophyllum nodosum) extract on shoot and root dry mass accumulation of plantlets budding from segments taken from apical, medial and basal parts of culms of the RB867515 variety. The experiment was a 3 x 2 factorial (three culm sections x kelp extract applied at 2.0 l.ha -1 and control) at the Sugar Cane Research Station at the Federal University of Paran, Brazil. Results showed improvement in shoot and root dry mass accumulation in plantlets budding from the basal part of culms following treatment with the A. nodosum kelp extract.

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 score0.003
Threshold uncertainty score0.005

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 integrity0.0000.000
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 head0.089
GPT teacher head0.338
Teacher spread0.249 · 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

Citations9
Published2015
Admission routes1
Has abstractyes

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