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Record W3203529016 · doi:10.13031/aim.20162455669

Modeling of Heating Requirement in Chinese Solar Greenhouse

2016· article· en· W3203529016 on OpenAlexfundno aff
Md Shamim Ahamed, Huiqing Guo, Karen Tanino

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGreenhouse Technology and Climate Control
Canadian institutionsnot available
FundersInnovation SaskatchewanNational Aeronautics and Space Administration
KeywordsGreenhouseEnvironmental scienceTranspirationHeat transferEnergy balanceSolar greenhouseThermal energy storageHeat sinkSolar energyAtmospheric sciencesMeteorologyMechanicsThermodynamicsMechanical engineeringPhotosynthesisEngineeringChemistryPhysicsBotany

Abstract

fetched live from OpenAlex

Abstract. A mathematical model is developed for simulation of the heating requirement in Chinese solar greenhouses. The model was developed based on heat balance of the greenhouse air that takes into account all of the heat sources and sinks and transfers mechanisms including the variation in solar radiation, ventilation and infiltration, heat storage capacities of the north wall and the ground, and heat exchanged in the process of plant photosynthesis and transpiration. The soil surface temperature and north wall surface temperature are estimated by solving the ordinary differential equations of heat balance equation of the north wall and the greenhouse floor. The model would be beneficial to the researchers and greenhouse industry for predicting the time-dependent heating requirement in Chinese solar greenhouses.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.229
Teacher spread0.207 · 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 designSimulation or modeling
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

Citations6
Published2016
Admission routes1
Has abstractyes

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