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Record W7028626478

Feature Story: Students show off mobile computer apps

2015· other· en· W7028626478 on OpenAlexaboutno aff

Bibliographic record

VenueoURspace (University of Regina) · 2015
Typeother
Languageen
FieldPhysics and Astronomy
TopicElectrical and Electromagnetic Research
Canadian institutionsnot available
Fundersnot available
KeywordsMobile appsMobile deviceMobile computingGeneral partnershipFeature (linguistics)Style (visual arts)
DOInot available

Abstract

fetched live from OpenAlex

Computer science students at the University of Regina recently had the chance to display mobile apps they developed – with a prize of $3,000 on the line, thanks to sponsorship from ISM Canada. The event, a partnership between the University of Regina and ISM, was modeled loosely on the TV show Dragons’ Den that included a celebrity panel. “Competing for this award allows the top students in the Mobile Computing course to showcase the work they have been doing this semester. Presenting and discussing their projects in this Dragons’ Den style gives them valuable experience in communicating their work to a broad audience,” explains Dr. Orland Hoeber, Associate Professor of Computer Science and instructor of the CS 455 and CS 855 courses on Mobile Computing.

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)0.001
metaresearch head score (Gemma)0.003
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.186
Threshold uncertainty score0.623

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.1860.090

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 head0.008
GPT teacher head0.228
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

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

Citations0
Published2015
Admission routes1
Has abstractyes

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