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Record W4384698228 · doi:10.22215/etd/2023-15638

Transforming Ocean Plastics into 3D Printed Islands - A Speculative Project for Areas Suffering from Rising Sea Levels

2023· dissertation· en· W4384698228 on OpenAlexaff
Corina Amarioarei

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsCarleton University
Fundersnot available
KeywordsFactory (object-oriented programming)Land reclamation3d printedGarbageScale (ratio)Lead (geology)Environmental scienceProduct (mathematics)EngineeringEnvironmental resource managementOceanographyGeographyArchitectural engineeringComputer scienceWaste managementGeologyArchaeologyManufacturing engineeringCartography

Abstract

fetched live from OpenAlex

This thesis investigates the architectural potential of transforming ocean plastics into 3D printed islands.Purely speculative, the project proposes an alternative use for excess plastics that can positively impact the environment.Two interventions are proposed:The Factory is a structure positioned in the Great Pacific Garbage Patch.It takes advantage of the ocean's natural currents to collect and prepare plastics for 3D printing.The second, The Islands, are the 3D printed product of The Factory and the focus of the thesis.They are envisioned to be dispatched to areas suffering from rising sea levels for land reclamation.Emphasis is placed on designing a form that maximizes the ecological opportunity for biodiversity both within aquatic and terrestrial environments.The creation of multiple islands using ocean plastics begins to put a scale to the catastrophic amount of pollution.Prototypes are developed to test criteria of interest and inform the design direction.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.269
Teacher spread0.246 · 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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