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Record W4390103189 · doi:10.5267/j.ijiec.2023.9.007

Collaborative decision making of photovoltaic industry chain considering carbon quota sharing contract

2023· article· en· W4390103189 on OpenAlexvenueno aff
Jun Hu, Jie Wu

Bibliographic record

VenueInternational Journal of Industrial Engineering Computations · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsnot available
Fundersnot available
KeywordsPhotovoltaic systemBusinessIndustrial organizationEnvironmental economicsEconomicsEngineering

Abstract

fetched live from OpenAlex

From the perspective of carbon quota policy, we consider integrating carbon quota sharing contracts into the collaborative decision-making model of the photovoltaic industry chain and compare and explore the collaborative decision-making of the photovoltaic industry chain under decentralized decision-making and considering carbon quota sharing contracts. Research has found that carbon quota sharing contracts can effectively promote green innovation among the main body of the photovoltaic industry chain; In the case of carbon quota sharing contracts, the pricing between photovoltaic system suppliers and photovoltaic power plant enterprises is lower; Under the carbon quota sharing contract, the profits, and overall profits of each entity in the photovoltaic industry chain are better than the optimal profits under decentralized conditions.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.199
Threshold uncertainty score0.612

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.330
Teacher spread0.297 · 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 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

Citations2
Published2023
Admission routes1
Has abstractyes

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