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Record W7003332825

Call of Silence

2023· article· en· W7003332825 on OpenAlexaff

Bibliographic record

VenuecIRcle (University of British Columbia) · 2023
Typearticle
Languageen
FieldComputer Science
TopicData Analysis with R
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSilenceBeautyFocus (optics)Graduation (instrument)BlindnessPerspective (graphical)PerceptionDoors
DOInot available

Abstract

fetched live from OpenAlex

In contemporary society, individuals with disabilities are highly valued, yet the design of parks and public spaces catering to the visually impaired remains uncommon. People with visual impairments can be found in every corner of our communities. It is crucial to ensure that they have access to a supportive environment that fosters physical and mental well-being and enables them to explore the beauty of nature and society. The focus of this graduation project is to create designs that cater to the needs of the visually impaired, allowing them to fully engage with their surroundings. Nature awareness is often visual, relying on the lush green scenery that surrounds us. However, my project, “Call of Silence,” aims to expand our understanding of nature beyond the visual realm, creating a multi-sensory experience that can be enjoyed by everyone, including those with visual impairments.

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)0.005
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.965
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.045
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0070.007
Scholarly communication0.0070.005
Open science0.0020.010
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0350.009

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 head0.010
GPT teacher head0.179
Teacher spread0.170 · 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.

Study designNot applicable
Domainnot available
GenreOther

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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