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Record W4391210341 · doi:10.1145/3623509.3634740

Making Biomaterials for Sustainable Tangible Interfaces

2024· article· en· W4391210341 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsCarleton University
FundersUniversitas Brawijaya
KeywordsBioplasticVariety (cybernetics)Computer scienceStudioBiomaterialHuman–computer interactionEngineeringNanotechnologyEngineering ethicsMaterials science

Abstract

fetched live from OpenAlex

In this studio, we will explore sustainable tangible interfaces by making a range of biomaterials that are bio-based and readily biodegradable. Building off of previous TEI studios that were centered around one specific biomaterial (i.e., bioplastics at TEI’22 and microbial cellulose at TEI’23), this studio will provide participants the ability to experience a wide variety of biomaterials from algae-based bioplastics, to food-waste-based bioclays, to gelatin-based biofoams. We will teach participants how to identify types of biomaterials that are applicable to their own research and how to make them. Through hands-on activities, we will demonstrate how to implement biomaterials in the design of sustainable tangible interfaces and discuss topics sensitized by biological media such as more-than-human temporalities, bioethics, care, and unmaking. Ultimately, our goal is to facilitate a space in which HCI researchers and designers can collaborate, create, and discuss the opportunities and challenges of working with sustainable biomaterials.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.907
Threshold uncertainty score0.616

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 communication0.0010.001
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 head0.049
GPT teacher head0.363
Teacher spread0.314 · 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

Quick stats

Citations18
Published2024
Admission routes1
Has abstractyes

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