U.S.S. Alba: evaluation cards for pupils, teachers, and parents/guardians
Bibliographic record
Abstract
"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 & 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. 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!
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.270 | 0.134 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".