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U.S.S. Alba: evaluation cards for pupils, teachers, and parents/guardians

2021· other· en· W6920743104 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2021
Typeother
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsOutreachWindow (computing)Work (physics)Series (stratigraphy)Quarter (Canadian coin)

Abstract

fetched live from OpenAlex

"U.S.S. Alba" is a series of forensics workshops adapted for primary school audiences as part of Glasgow Children's University "Thinking Inside The Box" project. It was funded by the Royal Society of Chemistry Outreach Fund and the University of Strathclyde Alumni Fund, and supported by staff and students of the Department of Pure &amp; Applied Chemistry, University of Strathclyde. Dr Kirsty Ross created the original iteration which was for S1/S2 pupils as part of Prestwick Airport STEM week. This version splits up the activities into 3/4 lessons, including one homework task. Topics include: fingerprinting, blood type analysis, mysterious powders, thin layer chromatography, and DNA analysis. These are the evaluation cards that we used for the project. The blue side should be filled in at the start of the session. The grey side is filled in at the end of the series of lessons.<br>The credit for the original inspiration lies with Lewis Hou of www.scienceceiligh.com, who pioneered the format with his Leith Labs feedback cards. Thank you Lewis!

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: Other · Consensus signal: none
Teacher disagreement score0.464
Threshold uncertainty score0.846

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)0.1550.000

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 head0.059
GPT teacher head0.325
Teacher spread0.266 · 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
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
Published2021
Admission routes1
Has abstractyes

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