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Record W2019995008 · doi:10.1115/ipc2004-0765

Managing Climate Change Risk: Emerging Financial Sector Expectations

2004· article· en· W2019995008 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.

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

Venue2004 International Pipeline Conference, Volumes 1, 2, and 3 · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Sustainable Development
Canadian institutionsnot available
Fundersnot available
KeywordsBenchmarkingClimate changeBusinessFinancial sectorEnergy sectorQuarter (Canadian coin)Risk managementFinanceFinancial riskEmerging marketsNatural resource economicsEconomicsGeographyMarketing

Abstract

fetched live from OpenAlex

During the third quarter of 2003, Eos Research & Consulting Ltd. conducted a two part study examining emerging standards for how energy companies manage climate change related risks. The first part was a survey of financial institutions in Canada, U.S. and internationally to determine their expectations for how energy companies should approach risks associated with climate change and policies to address it. In a parallel effort, using criteria which were based in part on the results from the financial sector survey, eleven leading energy companies were compared in a benchmarking study which examined response to climate change risks to date. The result provided two facets of the emerging standard for climate change risk management in the energy sector. This paper examines the results of the financial sector survey, drawing conclusions about the role that sector will play in setting expectations for how energy companies respond to climate change risks in the foreseeable future.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.247
Teacher spread0.227 · 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