Bibliographic record
Abstract
Post-secondary engineering students havedifficulty with course concepts due to disconnect betweentheory and practice. Due to its co-op program, Universityof Waterloo students are at a unique position of beingable to put course knowledge into practice shortly afterclassroom exposure. Through the hands-on experiencegained from co-op, students are able to better understandcourse concepts. Case studies serve to replicate thepractical context provided by co-op and work, givingstudents an opportunity to see the real-life utilization ofthe concepts learned from lectures. Our exposure to casesin class greatly increased understanding of courseconcepts among my peers. Cases helped us realize thereal-life relevance of the theories learned in class,confusing information taught in class. As a case writer, Isaw the painstaking effort put into case development, toensure maximum effectiveness. Due to its ability toprovide practical application of knowledge within a shortamount of time, cases are an extremely valuableeducational tool for engineering students.
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 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 | 0.036 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.009 | 0.021 |
| Scholarly communication | 0.019 | 0.021 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".