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Record W2121381549 · doi:10.1155/2014/958521

A Review of Solar Photovoltaic Concentrators

2014· review· en· W2121381549 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Photoenergy · 2014
Typereview
Languageen
FieldEnergy
TopicSolar Thermal and Photovoltaic Systems
Canadian institutionsConcordia University
FundersDoğu Akdeniz Üniversitesi
KeywordsPhotovoltaic systemSunlightEnvironmental scienceSolar energySolar cablePhotovoltaic thermal hybrid solar collectorEngineering physicsCost reductionProcess engineeringComputer scienceMaterials scienceAutomotive engineeringOpticsElectrical engineeringPhysicsSolar mirrorEngineeringBusiness

Abstract

fetched live from OpenAlex

Throughout the recent centuries, the limits of using energy resources due to the cost and environmental issues became one of the scientists’ concerns. Because of the huge amount of energy received by the Earth from the sun, the application of photovoltaic solar cells has become popular in the world. The photovoltaic (PV) efficiency can be increased by several factors; concentrating photovoltaic (CPV) system is one of the important tools for efficiency improvement and enables for a reduction in the cell area requirement. The limits of the PV area can reduce the amount of absorbing irradiation; CPV systems can concentrate a large amount of sunlight into a smaller one by applying lenses or curved and flat mirrors. However, the additional costs on concentrating optics and cooling systems made CPV less common than nonconcentrated photovoltaic. This paper reviews the different types of PV concentrators, their performance with advantages and disadvantages, concentration ratio, acceptance angle, brief comparison between their efficiencies, and appropriate cooling system.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.911
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.328
Teacher spread0.300 · 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