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Record W2022779634 · doi:10.1109/mts.2012.2216592

Through the Glass, Lightly [Viewpoint]

2012· article· en· W2022779634 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

VenueIEEE Technology and Society Magazine · 2012
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPremiseWearable computerPoint (geometry)Quality (philosophy)Internet privacyWearable technologyComputer scienceAestheticsEpistemologyMathematicsArtPhilosophy

Abstract

fetched live from OpenAlex

I begin this article with the fundamental premise that wearable computing will fundamentally improve the quality of our lives [1]. I can make this claim because for the past 20 years I have been walking around with digital eye glasses (DEG), and I believe my life has been enhanced as a result. Perhaps I am biased about wearable computing, but like my EyeTap invention that computationally processes everything I see, I try to tell it like it is. I am of course, only a one person case study, but I know there are others out there who feel the same way as I do, and perhaps for very different reasons. It is well known that when traditional optical eyeglasses were first invented, many wearers of these eyeglasses were treated poorly and discriminated against. But as time went on, society began to accept eyeglasses, even to the point where they have, in some instances, become fashion statements. Many people, who have no need for spectacles, will purchase zero prescription eyeglasses just to look smart. This says a lot about technological innovation and how society responds to it over generations of varying levels of acceptance.

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 score0.914
Threshold uncertainty score0.293

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.271
Teacher spread0.252 · 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