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Record W1530732966 · doi:10.7202/1064029ar

'A Tale of Two Cities'

2010· article· en· W1530732966 on OpenAlexvenueno aff
Ralph E.H. Sims

Bibliographic record

VenueSens public · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsnot available
FundersMassey University
KeywordsCONTESTStatus quoPassionEnergy (signal processing)Sustainable energyPolitical scienceGlobal warmingAgency (philosophy)Ivory towerAtomic energyAction (physics)Climate changeMedia studiesEnvironmental ethicsSociologySocial scienceLawEngineeringPsychologyRenewable energyPhilosophySocial psychology

Abstract

fetched live from OpenAlex

There is no doubt that the issue of environment has become one of the most important of our generation. Whether people contest global warming with passion or want to preserve planet Earth with the most radical methods, the issue generates ardent debates that leave no one indifferent. After having spent nearly four years at the International Energy Agency in Paris, Ralph E. H. Sims has recently returned to his position as Professor of Sustainable Energy and Director of the Centre for Energy Research at Massey University in New Zealand. He is also an IPCC (Intergovernmental Panel on Climate Change) Co-ordinating Lead Author for several IPCC reports covering energy supply, integration and transport. In an essay based on a solid knowledge of the environmental issues and written with a dose of imagination and a touch of humour, he offers his perspectives on a rather dark future for those who prefer the status quo and a brighter one for those who defend a vigorous action in favour of the environment.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.032
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0250.016
Scholarly communication0.0180.016
Open science0.0020.016
Research integrity0.0060.017
Insufficient payload (model declined to judge)0.0320.010

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 head0.008
GPT teacher head0.217
Teacher spread0.209 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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
Published2010
Admission routes1
Has abstractyes

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