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Record W7007889485

Architectural succession: a multi-species approach to the built environment

2023· dissertation· en· W7007889485 on OpenAlexaboutno aff

Bibliographic record

VenueLu Zone Ul (Laurentian University) · 2023
Typedissertation
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsnot available
Fundersnot available
KeywordsBuilt environmentEcological successionProcess (computing)HabitatWildlifeFrame (networking)Natural (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

A novel approach to single-species design is urgently required. Urban expansion is directly \nimpacting global biodiversity, increasing habitat-threatened species reliance on human \ninfrastructure. Whereby recognizing the architect’s responsibility to provide habitat for \nadditional species, the built environment can be utilized for multi-species inhabitation. \nDerived from the natural cycle of ecological succession, Architectural Succession outlines \nthe process of change occurring for a built environments program and user over time. \nInformed by this framework, a Research Creation process examines the at-risk Chimney \nSwift and its food source within a successional multi-species structure. Further enhancing \nSudbury, Ontario’s, Regreening efforts, barren outcroppings offer significant opportunity \nfor multi-species built intervention, encouraging habitat recovery and the return of \nspecies at-risk. A wildlife observation pavilion explores the successional opportunities \nof traditional light wood frame construction undergoing the decomposition process to \nsupport the regrowth of the forest.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0030.009
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.022
GPT teacher head0.224
Teacher spread0.202 · 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 designTheoretical or conceptual
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
Published2023
Admission routes1
Has abstractyes

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