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Record W3217440393 · doi:10.1155/2021/2383473

Performance Prediction of the Ferrous Metal Smelting and Rolling Processing Industry in Supply-Side Structural Reform in China

2021· article· en· W3217440393 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

VenueJournal of Mathematics · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicGrey System Theory Applications
Canadian institutionsUniversity of Waterloo
FundersHumanities and Social Science Fund of Ministry of Education of China
KeywordsSmeltingOrder (exchange)Supply sideChinaNonferrous metalBusinessEconomicsEngineeringMetallurgyFinanceCommerceMaterials science

Abstract

fetched live from OpenAlex

Supply-side structural reforms and environmental protection policies have a great impact on the ferrous metal smelting and rolling processing industry. This paper uses a grey model that introduces a fractional-order cumulative generating operator to study the development of ferrous metal smelting and rolling processing enterprises under the influence of supply-side structural reform in order to derive the future development trend of the industry. The forecast results show that from 2018 to 2022, the number of enterprises and substitute enterprises, inventory, finished products, and assets and liabilities decreases; the scale of income of metal smelting and rolling processing industry increases. The results can serve as a reference for policy makers and industry investors.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.059
GPT teacher head0.334
Teacher spread0.275 · 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