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Record W1506240072 · doi:10.5539/jas.v7n7p64

Sustainability of Sisal Cultivation in Brazil Using Co-Products and Wastes

2015· article· en· W1506240072 on OpenAlexvenueno aff
Adalberto Cantalino, Ednildo Andrade Torres, Marcelo Santana Silva

Bibliographic record

VenueJournal of Agricultural Science · 2015
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa do Estado da Bahia
KeywordsSISALBioproductsBiofuelPulp and paper industrySustainabilityPulp (tooth)Life-cycle assessmentEnvironmental scienceTonneBiomass (ecology)BioenergyAgricultural engineeringMathematicsWaste managementEngineeringAgronomyProduction (economics)BiologyMaterials scienceEcology

Abstract

fetched live from OpenAlex

This work evaluates the potential of co-products from sisal fiber extraction and of plant residues at the end of the productive life cycle and their upgrading into bioproducts and biofuels, focus on Brazil, and, specifically on the Sisal Identity Territory in the state of Bahia. Sisal co-products and residues are identified and quantified; Environmental and socio-economic indicators are applied. Energy potential and bioproducts from sisal in Brazil have been studied in universities and research centers, but not sufficiently quantified, so the scientific bases for this purpose are still limited. Considering an annual sisal fiber production in Brazil at 100,000 MT, and a 4% yield from the fiber extraction process, an estimated 2.4 million metric tons of products are thus generated by the defibering process, consisting of pulp, sisal tow, and juice. Furthermore, an estimated 900,000 metric tons per year of residual biomass from the stems at the end of the 10-year productive cycle is produced and presently left to rot in the field.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.194
Threshold uncertainty score0.198

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.021
GPT teacher head0.302
Teacher spread0.280 · 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 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

Citations40
Published2015
Admission routes1
Has abstractyes

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