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Record W7139620270

Vol. 1 (2018): Galbraith Society Undergraduate Engineering Journal

2018· article· en· W7139620270 on OpenAlexfundno aff
Aanchal Aggarwal, Christopher Apostoli, Valeria Baranova, Holly (Wei) Chan, Lauren Chee, Luis E. Zhuo Chong, Alexander Yuheng Ding, Anston Emmanuel, Rabab Haider, Peter Zhi Xuan Li, Christopher Lucasius, Bogdan Raspopin, Yutong (Vivian) Ren, Andrew Tan, Annie Yang, Yang Silin, Marissa Zhang, Chris Zhu

Bibliographic record

VenueTSpace (University of Toronto) · 2018
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Pedagogy
Canadian institutionsnot available
FundersCanadian Armed ForcesStrong
KeywordsEngineering educationWork (physics)Science and engineeringEngineering economics
DOInot available

Abstract

fetched live from OpenAlex

Vol. 1 (2018): Galbraith Society Undergraduate Engineering Journal Published: 2018-06-25

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 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score0.996

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)0.0050.000

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 head0.012
GPT teacher head0.222
Teacher spread0.210 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2018
Admission routes1
Has abstractyes

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