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Record W2804766127 · doi:10.20361/dr29341

Artificial Eyes by B. Sheen

2018· article· en· W2804766127 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.

venuePublished in a venue whose home country is Canada.
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

VenueThe Deakin Review of Children s Literature · 2018
Typearticle
Languageen
FieldEngineering
TopicRobotics and Automated Systems
Canadian institutionsnot available
Fundersnot available
KeywordsParagraphSentencePresentation (obstetrics)Reading (process)NewspaperSubject (documents)White (mutation)Visual artsComputer sciencePsychologyArtArtificial intelligenceMedia studiesLinguisticsSociologyWorld Wide WebMedicinePhilosophy

Abstract

fetched live from OpenAlex

Sheen, Barbara. Artificial Eyes. Norwood House Press, 2017.Artificial Eyes is one of a series of non-fiction books called Tech Bytes, that “explores...new technologies and how they are changing the way people perform everyday tasks.” Barbara Sheen, author of almost 100 children’s books, explores the history of artificial eyes, how they are made, their effect on people’s lives, and future developments. This is a detailed work that is designed to be a reference or text book for Grades 4 – 6. It is an odd combination of factual presentation and anecdotal stories about individuals. For example, “When Teddy was two years old, he was diagnosed with a rare form of cancer in his eye. To rid him of the disease, his eye was surgically removed.” Squeamish children may find some content disturbing. To balance the dense text, most pages have a photograph, diagram, or side-bar containing interesting information. There are also “Did you know?” boxes, which allow for some level of interaction. For example, “Did you know? Bionic eyes only provide black-and-white vision. Experts are working on software that would let wearers see colors.” The end of each chapter also has text-based questions and potential research projects. In this way it is more like a text book, but it is unlikely that a classroom would need textbooks on a subject this specific.While the short sentence and paragraph structures are appropriate for the upper elementary reading level, many of the words and word-combinations will be difficult for students in these grades. They may require help in understanding the content. There are few children’s books about artificial eyes, so this would be a good addition to public libraries and both elementary and junior high school libraries. Recommended: 3 stars out of 4Reviewer: Sean C. BorleSean Borle is a University of Alberta undergraduate student who is an advocate for child health and safety.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.843
Threshold uncertainty score0.397

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 communication0.0000.000
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 head0.005
GPT teacher head0.225
Teacher spread0.220 · 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