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Record W2023934380 · doi:10.1016/j.egypro.2011.03.305

Canadian experience in low carbon eco-city development and the implications for China

2011· article· en· W2023934380 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

VenueEnergy Procedia · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicRemote Sensing and Land Use
Canadian institutionsnot available
Fundersnot available
KeywordsUrbanizationChinaUrban planningEnvironmental planningEnvironmental degradationEnvironmental protectionGeographyClimate changePopulationBusinessNatural resource economicsEnvironmental resource managementEnvironmental scienceEconomic growthEcologyCivil engineeringEngineeringEconomics

Abstract

fetched live from OpenAlex

Canada is a sparsely populated country with its majority of population concentrated in cities, and its urbanization rate had risen to 80.2% by 2006. A similar environmental situation (air and water pollution, biodiversity degradation, high carbon emissions, et al.) in Canada has been going on in China and many of the developing countries during urbanization process. Based on ideas from urban planning and ecological development, Canada has taken a series of effective eco-measures, which contain urban heat island effect mitigation program, green infrastructure construction, and livable region strategic planning, to tackle with the environmental problems. The accumulated experience provides positive reference for China to find ways confronting climate change and obstacles of low carbon eco-city development, including: (1) Low carbon eco-city development mode, (2) Urban green infrastructure, (3) Urban ecological planning, and (4) Public participation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.605

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)0.0000.000

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 head0.021
GPT teacher head0.200
Teacher spread0.179 · 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