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Record W4250747425 · doi:10.32920/ryerson.14647098

Energanic prototypes in the [post]-digital terrain

2021· preprint· en· W4250747425 on OpenAlexaff
Andrew Kaleva Hotari

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsArchitectureWorkspaceEnergy (signal processing)Process (computing)Work (physics)TerrainArchitectural engineeringComputer scienceHuman–computer interactionSociologyPolitical scienceEpistemologyData scienceEngineeringGeographyArtificial intelligenceVisual artsMechanical engineeringMathematicsArtCartography

Abstract

fetched live from OpenAlex

Although the direction of contemporary architectural thinking is heavily influenced by its critical engagement with energy usage, this relationship remains largely unexplored imaginatively. This thesis investigates an energy-centric approach to design that is enabled by digital workspace. By injecting energy transactions and modulations into otherwise abstract digital geometry while using analysis tools to examine their effects, the work is intended to speculate what this relationship with energy could be. For too long the application of emerging computer-based technologies in architecture have resisted critical agendas beyond idealist shape-making and form. At the same time the role of energy in the design process has been subsidiary and weak. Both fields of knowledge and their relationship to architecture are examined in a necessary marriage of mission and means. The research portion of this document concludes with a series of speculations that illustrate possible outcomes of the proposed energetic agenda.

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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score0.381

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 head0.007
GPT teacher head0.197
Teacher spread0.190 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2021
Admission routes1
Has abstractyes

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