MétaCan
Menu
Back to cohort
Record W4237299589 · doi:10.1002/div.3744

Terasen Inc

2006· article· en· W4237299589 on OpenAlexaboutno aff

Bibliographic record

VenueMergent s Dividend Achievers · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Governance and Law
Canadian institutionsnot available
Fundersnot available
KeywordsPipeline transportNatural gasFossil fuelPetroleumBusinessWastewaterSubsidiaryIrrigationEnvironmental scienceFinanceEngineeringEnvironmental engineeringWaste managementGeology

Abstract

fetched live from OpenAlex

Abstract Oil and Gas (MIC: 14.2 SIC: 1623 NAIC: 486910) Terasen is a provider of energy transportation and utility services. Through Terasen Gas, Co. distributed natural gas in British Columbia (B.C.) to more than 875,000 customers in more than 125 communities at Dec 31 2004. Through Terasen Pipelines, Co. provides petroleum transportation services from Edmonton, Alberta to Vancouver, B.C., Washington state, the U.S. Rocky Mountains region and the U.S. midwest. Terasen Water and Utility Services, subsidiaries of Co., are providers of water and wastewater treatment services as well as product sales related to the water, sewer and irrigation markets, operating over 90 systems in more than 50 communities throughout B.C., Alberta and Alaska.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.010
GPT teacher head0.182
Teacher spread0.172 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueMergent s Dividend AchieversSame topicCorporate Governance and LawFrench-language works237,207