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Record W4416702475 · doi:10.1145/3773967.3773974

A Review of Assets'2024 from a Newbie Academic

2025· article· en· W4416702475 on OpenAlex
Martin Lettry

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueACM SIGACCESS Accessibility and Computing · 2025
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsBachelorSession (web analytics)Academic communityWork (physics)

Abstract

fetched live from OpenAlex

My name is Martin Lettry, I'm a master's student in Computer Science at EPFL in Switzerland and an alumnus of the University of Lugano (USI), also in Switzerland. My academic journey has been significantly impacted by my collaboration with LighthouseTech – a startup developing smart glasses for blind and visually impaired (BVI) people. As part of my bachelor thesis, I focused on defining default settings for these glasses through user testing with BVI individuals in Milan and Bern. My decision to attend ASSETS'24 in St. John's, Newfoundland, was driven by several objectives. First and foremost, I wanted to present my research through a poster session showcasing my bachelor thesis and a device prototype. Additionally, I was curious to see first-hand some of the research being done in the accessibility community and learn about ongoing projects. Given my background in BVI research, I was particularly interested in connecting with other researchers working on similar solutions.

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)0.005
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: Empirical
Teacher disagreement score0.557
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.070
GPT teacher head0.395
Teacher spread0.325 · 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