Refining in the Americas: not enough firm projects
Bibliographic record
Abstract
Countries throughout the Western Hemisphere face shortages of refinery capacity, but too few schemes are making it past the drawing‐board. OET's latest refining survey (see Table E ) shows a large number of projects but many remain tentative and lack firm locations and completion dates: not to mention planning approval and financial backing. Western Hemisphere: Proposed new refineries Year Company Refinery Capacity On‐stream (th bpd) Canada Beaver Hills Edmonton, Alta 37 N/A Irving Oil Saint John, NB 300 2015 NLR Placentia Bay, Nfld 300 2010 Valero Quebec 50* 2008 USA ACFY Yuma, Az 150 2011 Calumet NE Utah 20 N/A Chevron Pascagoula, Ms 270* N/A Hyperion S Dakota 400 N/A KPC Louisiana 600 N/A Lazarus Church Point, La 20 2009 Lazarus Mermantau, La 20 2009 Lazarus Longview, Tx 30 2009 Motiva Port Arthur, Tx 325* 2010 Sinclair Tulsa, Ok 45* 2010 Argentina N/A N/A 150 N/A Brazil Petrobras NE Brazil 200 2010 Petrobras N/A 500 2014 Colombia Ecopetrol/Glencore Cartagena 65* 2011 Ecuador Petroecuador/PDVSA Manabi 300 N/A Mexico Pemex N/A 230 N/A Nicaragua PDVSA N/A 150 N/A Peru Petroperu Talara 45* N/A Venezuela PDVSA Caripito 200 2009 PDVSA San Diego 400 2009 PDVSA/Lukoil Orinoco 60 N/A 1Q Average 9.7 * Expansion of existing plant. Figures refer to new capacity N/A: not available All dates and capacities approximate and subject to change Source: 'The Month in Brief' (various); oil press
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.004 |
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".