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Record W4235001845 · doi:10.26855/ijfsa.2020.12.001

A Parabolic Trough Baking Device Developed in Lesotho

2020· article· en· W4235001845 on OpenAlexfundno aff
Ivan Yaholnitsky

Bibliographic record

VenueInternational journal of food science and agriculture · 2020
Typearticle
Languageen
FieldEngineering
TopicSmart Parking Systems Research
Canadian institutionsnot available
FundersMcGill University
KeywordsParabolic troughTrough (economics)Materials scienceEnvironmental scienceGeographyEconomicsThermalMeteorologyKeynesian economics

Abstract

fetched live from OpenAlex

This paper describes technical, operational and financial metrics related to a parabolic trough solar cooking device first developed by the author in 2004 in Lesotho.It is a baking tube with a diameter of 200mm which lies in the focus of the parabolic trough and has an overall 10:1 concentration ratio.The device has been in continuous use since then, along with other ovens of the same type, primarily used for baking in the framework of a small cottage bread baking application.The paper describes the physical characteristics of the solar oven and its operating context.The materials and precise geometry employed is examined, along with innovations applied over the course of many years of development.As well, shop procedures for manufacture are described along with operating experience, in terms of doing applied commercial work in an authentic setting.The conclusion summarizes financial indicators, costs and potential revenues, return on investment, and prospective for scaling, extension and replication, along with contemporary linkages to the Sustainable Development Goals and energy parameters in Lesotho.

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 score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.036
GPT teacher head0.287
Teacher spread0.250 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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