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Record W2087626425 · doi:10.17722/ijrbt.v4i3.257

Coffee Clusters in Brazil

2014· article· en· W2087626425 on OpenAlexvenueno aff
Marly Cavalcanti

Bibliographic record

VenueInternational Journal of Research in Business and Technology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicRural Development and Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

What is organic coffee? Basically, organic coffee is a coffee produced without using highly soluble chemical and either of fungicides, herbicides, insecticides or other chemicals. A specialty coffee is characterized by being differentiated quality, which involves from the process of production to consumption itself. There is no precise definition of the product and to establish a more approximate characterization should consider intrinsic parameters of the quality of the drink (variety, origin, and post-harvest cultural), as well as the condition of grain production. In Brazil, the entity responsible for evaluation, qualification, certification and promotion of coffee is the ABIC. When it comes to specifically special coffee, BSCA (Brazil Specialty Coffee Association) or Brazil Specialty Coffee Association) undertakes to assess and qualify products as rigid standard of evaluation. The coffee industry is represented by 300 thousand properties of various sizes (23 are small businesses). The sector employs 8.4 million workers directly and indirectly, that add a gross value of production of R$ 5 billion to the national economy. An important entry barrier lies in product differentiation via production process, with emphasis on the adoption of organic products and practices to better qualify the resulting coffee. There are several cases of producers who converted their crops to produce higher-quality coffees. At this point, the investment in training and in techniques and equipment is fundamental to obtaintion of a product special.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.200
Threshold uncertainty score0.397

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0040.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0150.001

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 head0.013
GPT teacher head0.309
Teacher spread0.296 · 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
Published2014
Admission routes1
Has abstractyes

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