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Record W2101820017 · doi:10.6000/1927-5129.2013.09.39

Design and Development of Efficient Domestic Electric Cum Solar Oven

2013· article· en· W2101820017 on OpenAlexvenueno aff
Aamir Shahzad

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2013
Typearticle
Languageen
FieldEnergy
TopicSolar Thermal and Photovoltaic Systems
Canadian institutionsnot available
Fundersnot available
KeywordsSolar energyElectricityEnvironmental scienceThermostatProcess engineeringEngineeringMechanical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

An improved design is proposed to investigate the characteristic study of an electric cum solar oven (ECSO) using circular cover in which both solar energy and electricity have been utilized as energy source for different food items. The newly designed solar oven has been fabricated by employing indigenous raw materials and it provides more reliable performance than the previously used solar oven for cooking of agricultural products and conventional food items. The new observations show that the cooking process of products is dependent on both the circular shape and climate conditions. The electrical heating has been used in combination with the solar energy to enhance the oven heating during the periods of lesser sunshine. The base of the oven was made up of the electric heating plate that is controlled by timer and an electric thermostat is used to control the heating of the oven. The performance and parameters obtained from the newly designed solar oven are found to be excellent than that obtained from previously known solar ovens for cooking of various edibles. It is shown that this newly designed solar oven can be efficient for cooking and preservation of all edible stuffs and appearance of cooked food products. The performance of the solar cooker has been checked under the local climate conditions of Faisalabad city to observe its efficiency with satisfactory results.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.023
GPT teacher head0.236
Teacher spread0.213 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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