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Record W2780804778 · doi:10.1007/s10113-017-1263-9

Energy flows in the coffee plantations of Costa Rica: from traditional to modern systems (1935–2010)

2017· article· en· W2780804778 on OpenAlexfundno aff
Juan Infante‐Amate, Wilson Picado Umaña

Bibliographic record

VenueRegional Environmental Change · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsnot available
FundersMinisterio de Economía y CompetitividadBanco SantanderSocial Sciences and Humanities Research Council of CanadaFundación Banco Santander
KeywordsProductivityContext (archaeology)Biomass (ecology)EcosystemAgricultureInvestment (military)Agricultural economicsAgroforestryNatural resource economicsEnvironmental scienceEconomicsGeographyEcology

Abstract

fetched live from OpenAlex

This article addresses energy flows in the coffee agro-ecosystems of Costa Rica within the context of the socio-ecological transition, between 1935 and 2010, accounting for the shift from traditional to modern tropical agriculture. Estimating indicators of energy efficiency in crop management makes it possible to analyze the changing productive rationality of growers by studying end uses of all biomass appropriated from coffee agro-ecosystems. Coffee land and labor productivity, as expected, multiplied (by factors of 2.01 and 1.56, respectively). However, considering total biomass produced in coffee agro-ecosystems, productivity did not display such a significant increase. In contrast, all other energy efficiency indicators declined. Final energy return on investment (FEROI) fell from 1.02 in 1935 to 0.51 in 2005. External final EROI fell even farther, from 18.90 down to 1.86. The socio-ecological transition brought about the loss of multifunctionality in the final use of products derived from coffee agro-ecosystems, as new products replaced traditional ones.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score0.815

Codex and Gemma teacher scores by category

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 science0.0010.000
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 head0.117
GPT teacher head0.238
Teacher spread0.121 · 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 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

Citations21
Published2017
Admission routes1
Has abstractyes

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