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Record W4307879469 · doi:10.18357/otessac.2022.1.1.97

The Lymphatic System of the Dog: Translating and Transitioning to an Open Textbook

2022· article· en· W4307879469 on OpenAlexaffvenueabout
Kristine Dreaver‐Charles, Monique N Mayer

Bibliographic record

VenueThe Open/Technology in Education Society and Scholarship Association Conference · 2022
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSituatedPublishingWork (physics)SociologyLibrary scienceQuality (philosophy)PedagogyComputer sciencePolitical scienceEngineeringLaw

Abstract

fetched live from OpenAlex

This contribution is situated at the University of Saskatchewan, where Open Education Resources have been supported since 2014. During the pandemic we began the work of translating The Lymphatic System of the Dog, by Dr. Hermann Baum, into English. Originally published in 1918, Dr. Baum’s book has been transitioned into Pressbooks, with the addition of ancillary resources. Balancing the legacy of Dr. Baum’s research with our own innovations in assessment and design engages new generations of learners and practitioners. The benefits for faculty and students in designing and publishing openly must also be acknowledged. Locally designed and produced open education resources created with and by our university community is of significance to the academy. The adoption of open textbooks in university classes establishes a discourse and refinement of knowledge ensuring quality resources are designed and shared.

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)0.013
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.045
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.009
Scholarly communication0.0170.011
Open science0.0020.011
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0080.004

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 head0.027
GPT teacher head0.310
Teacher spread0.283 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2022
Admission routes3
Has abstractyes

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