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Record W4409699293 · doi:10.22215/cujs.v3i2.5109

NSCI1000 Redesigned: CuPortfolio Edition

2025· article· en· W4409699293 on OpenAlexaff
Mahnoor Nadeem, Katie Lucas

Bibliographic record

VenueCarleton undergraduate journal of science. · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

In order to promote reflective and integrated learning and explore the interconnectedness and significance of themes discussed in science courses, CuPortfolio, Carleton University’s ePortfolio system, was utilized. This involved the redesign of the Seminar in Science courses, which aimed to provide a cross-disciplinary examination of contemporary scientific issues, with an emphasis on employing interdisciplinary approaches to problem-solving. The course was structured into four interconnected thematic units: Critical Thinking, Community Building, Experiential Learning, and Equity, Diversity, and Inclusion (EDI). This initiative is supported by the recognition of ePortfolios as a high-impact practice that enhances students’ ownership of their learning. Additionally, students were encouraged to use CuPortfolio to create multimedia portfolios, facilitating the connection of explored ideas.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.330
Threshold uncertainty score0.955

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.3300.130

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 head0.381
Teacher spread0.362 · 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.

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
Published2025
Admission routes1
Has abstractyes

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