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Record W2970778568 · doi:10.13073/fpj-d-19-00022

Gravity Models of China's Bamboo and Rattan Products Exports: Applications to Trade Potential Analysis

2019· article· en· W2970778568 on OpenAlex
Li Huang, Ke Chen, Mi Zhou, Brendan Nuse

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueForest Products Journal · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBamboo properties and applications
Canadian institutionsnot available
Fundersnot available
KeywordsRattanBambooChinaGravity model of tradeProduct (mathematics)BusinessAgricultural economicsPopulationGeographyInternational tradeEconomicsBotanyMathematicsBiologyDemography

Abstract

fetched live from OpenAlex

Abstract Using export panel data for China and 24 bamboo and rattan trading partners from 2007 to 2017, this study simulates the export trade of Chinese bamboo and rattan products using a gravity model. Our results showed that economic size has a significant positive impact on the bilateral trade of bamboo and rattan products, while absolute distance between two major economic centers and population size have a significant negative impact. Furthermore, relevant Asia-Pacific Economic Cooperation (APEC) trade arrangements have an impact on bamboo and rattan product trade flows from China. Meanwhile, trade of bamboo and rattan between China and APEC countries such as South Korea, Canada, Russia, and Thailand shows much room for growth.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score0.232

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.016
GPT teacher head0.214
Teacher spread0.198 · 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