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Record W3153428987 · doi:10.14288/1.0390872

Plastic Metabolism in a Garbage Apocalypse

2020· article· en· W3153428987 on OpenAlexaboutno aff
Emily A. Kazanowski

Bibliographic record

VenuecIRcle (University of British Columbia) · 2020
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Environmental Waste Management
Canadian institutionsnot available
Fundersnot available
KeywordsGarbageComputer scienceProgramming language

Abstract

fetched live from OpenAlex

We have a plastic waste crisis. Our waste is concealed in bins, taken out to back lanes, buried at the landfill or shipped overseas. We have become increasingly expert at physically distancing ourselves from our waste. Spaces for waste are not for humans. Waste is invisible to us. Plastic Metabolism in a Garbage Apocalypse operates within a fictional, yet plausible, garbage strike. This strike brings the global waste crisis home, registering it at the scale of a household. How do we cope? Our perceptions must shift if we are to escape the constricting infill of waste in our previously pristine domestic realms. We must see waste as a raw material. This project proposes a new system of construction, operating on the existing body of the Vancouver Special, a locally specific and common housing typology. Domestic spatial relationships are re-imagined establishing an intimate relationship between the human body and waste material and processes. Building with waste is imperative. We must see waste as an opportunity, and allow new growth through the reconstitution of waste materials. Using a playful and optimistic perspective, Plastic Metabolism in a Garbage Apocalypse allows the messy and uglier sides of human life to support a productive domestic environment.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.918
Threshold uncertainty score0.974

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 head0.014
GPT teacher head0.186
Teacher spread0.172 · 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 designObservational
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
Published2020
Admission routes1
Has abstractyes

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