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Record W7065171234

Disturbance/Intersection

2016· dissertation· en· W7065171234 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2016
Typedissertation
Languageen
FieldEngineering
TopicPower Transformer Diagnostics and Insulation
Canadian institutionsnot available
Fundersnot available
KeywordsIntersection (aeronautics)Natural (archaeology)Natural landscapeField (mathematics)Landscape designDisturbance (geology)Representation (politics)
DOInot available

Abstract

fetched live from OpenAlex

This practicum outlines a conceptual design proposal for the intersection of Provencher Boulevard and Archibald Street, in Winnipeg, Manitoba. The goal of the proposed intersection design is to assemble three sites at the intersection of Provencher Boulevard and Archibald Street that allows active transportation, public transport and vehicular subjects to coexist in the landscape with their related activities. Disturbance theory is discussed as a framework to the practicum as it relates to physical adaptations in the landscape in response to natural events and human activities. In conclusion, applying the concept of disturbance to the field of landscape architecture may allow a site to positively adapt to both predictable and unpredictable natural events and/or human activities.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.088
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.010
Scholarly communication0.0060.002
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0140.002

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 head0.006
GPT teacher head0.175
Teacher spread0.169 · 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
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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