Relationship between national and international wood prices
Bibliographic record
Abstract
This work analyses the Canadian sawn wood price impact on the price building of the sawn wood in booth São Paulo and Pará states Price conveyance between those states was also assessed KPSS tests results show that all price series are order 1I stationary Johansen`s test results show that none of the price series is co-integrated It can be concluded that there is no special integration between Canadian and Brazilian States` (São Paulo and Pará) wood markets that is a demand shock in any of those markets is not likely to affect wood prices in other markets Another conclusion led to by Granger´s Causality Test is that Granger arisen by Canadian prices influence on Pará´s prices the same way as Granger Pará`s prices influence upon São Paulo`s prices These findings show the market view since Canadian the world´s main sawn wood exporter has influenced upon Pará a great Brazilian sawn wood producer Yet because São Paulo´s civil construction consumes Pará´s wood in large scale Pará´s prices have great influence on São Paulo´s Therefore results suggest that Brazilian wood market in not effective at long term as there in no evidence of long term co-integration what does not litter allow either arbitrage mechanisms or unique prices law to work as they have been expected.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".