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Record W4246502175 · doi:10.24124/2003/bpgub259

Institutional barriers to climate responsive design in commercial redevelopment in Prince George, British Columbia.

2003· dissertation· en· W4246502175 on OpenAlexaffabout
Laura Ryser

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsBibliothèque et Archives nationales du QuébecCanadian Association of GeographersUniversity of Northern British ColumbiaUniversity of Waterloo
Fundersnot available
KeywordsGeorge (robot)RedevelopmentArtArt historyEnvironmental ethicsPolitical scienceEngineeringCivil engineeringPhilosophy

Abstract

fetched live from OpenAlex

de reproduire, prêter, distribuer ou vendre des copies de cette thèse sous la forme de microfiche/film, de reproduction sur papier ou sur format électronique.L'auteur conserve la propriété du droit d'auteur qui protège cette thèse.Ni la thèse ni des extraits substantiels de celle-ci ne doivent être imprimés ou autrement reproduits sans son autorisation.

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)0.007
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score0.551

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.003
Scholarly communication0.0050.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.011
GPT teacher head0.269
Teacher spread0.258 · 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 designQualitative
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
Published2003
Admission routes2
Has abstractyes

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