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Record W4377136786 · doi:10.1016/j.ijft.2023.100380

Effect of using phase change materials on thermal performance of passive solar greenhouses in cold climates

2023· article· en· W4377136786 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 Thermofluids · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGreenhouse Technology and Climate Control
Canadian institutionsToronto Metropolitan UniversityOntario Tech University
Fundersnot available
KeywordsPassive solar building designGreenhouseEnvironmental sciencePhase changeThermalSolar energyThermal energy storageAtmospheric sciencesMaterials sciencePhase-change materialMeteorologyEngineering physicsEnvironmental engineeringEngineeringGeographyThermodynamicsAgronomyPhysics

Abstract

fetched live from OpenAlex

Passive solar greenhouses are crucial for sustainable agriculture in cold regions, but they face challenges in temperature regulation, especially at night when temperatures drop down significantly. Phase Change Materials (PCMs) appears to be a potential solution to improve the thermal stability by storing and releasing large amounts of thermal energy during phase changes. In the present study, it is obtained that incorporating PCMs into the north wall of a passive solar greenhouse helps extend the growing season by up to 48 days, increase the average temperature during the growing season from 12.1 °C to 24.8 °C, and enable a wider range of crops to be cultivated. This study provides valuable insights into the feasibility of using PCMs in passive solar greenhouses to improve temperature regulation and energy efficiency in cold climates.

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)0.000
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 score0.045
Threshold uncertainty score0.174

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.032
GPT teacher head0.299
Teacher spread0.267 · 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