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Record W7140149876

OER by Discipline: UCalgary

2022· book· en· W7140149876 on OpenAlexfundaboutno aff
Sarah Adams, Ramina Mukundan

Bibliographic record

VenueOpen MIND · 2022
Typebook
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsnot available
FundersBritish Columbia Institute of TechnologyStockholms UniversitetKwantlen Polytechnic UniversityWilfrid Laurier UniversityUniversity of CalgaryUniversity of Minnesota
KeywordsOpen educational resourcesSubject (documents)Educational resourcesQuality (philosophy)Key (lock)AttributionCommons
DOInot available

Abstract

fetched live from OpenAlex

The OER by Discipline Guide: University of Calgary developed by Libraries and Cultural Resources staff supports faculty locate quality open educational resources in their subject area by providing curated lists of OER organized according to the faculties, departments, and subjects at UCalgary. The Open Educational Resources within this guide have been evaluated by faculty, librarians, and other relevant parties prior to inclusion. The lists of OER in each discipline are not intended to be comprehensive, but rather to provide a sample of the key resources available. This guide will be updated periodically as new resources are identified, evaluated, and adopted. This book is a cloned version of OER by Discipline: University of Manitoba edited by University of Manitoba Libraries is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted. It has been adapted from the original source. This is a static version of the text; the live Pressbooks version can be accessed via https://openeducationalberta.ca/oerguideucalgary/

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 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 categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.110
Threshold uncertainty score1.000

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 communication0.0010.001
Open science0.0040.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0470.005

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 head0.308
Teacher spread0.281 · 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; both teacher heads agree on what is shown here.

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".

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Citations0
Published2022
Admission routes2
Has abstractyes

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