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Record W2546984397 · doi:10.1145/2957276.2957301

Barriers to Using, Customizing, and Printing 3D Designs on Thingiverse

2016· article· en· W2546984397 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 institutionsUniversity of Waterloo
Fundersnot available
Keywords3D printingWorkflowComputer scienceMetadataDownload3d printedHuman–computer interactionWorld Wide WebKey (lock)MultimediaEngineeringDatabaseComputer security

Abstract

fetched live from OpenAlex

Thingiverse is the largest 3D design-sharing online community with millions of users. Thingiverse provides a low-barrier-to-entry for exploring 3D printing as users can quickly download premade 3D designs and ask design-specific questions. In this paper, we investigate users' activities on Thingiverse and their conversations by using quantitative and qualitative analyses. Our findings shed light on various barriers in using, customizing, and printing premade 3D designs. The results suggest that although Thingiverse plays a key role in helping users get started with basic 3D printing, there are many opportunities to streamline the design-download-customize-print workflows. In particular, opportunities exist for designers to provide richer metadata, clarifications, and expert tips to help users succeed in printing objects and customizing existing 3D designs.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.644
Threshold uncertainty score0.291

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 communication0.0000.001
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 head0.041
GPT teacher head0.294
Teacher spread0.253 · 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

Citations56
Published2016
Admission routes1
Has abstractyes

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