Bibliographic record
Abstract
In this episode, two University of Windsor Outstanding Scholars Students Grace Taylor and Krishali Kumar interview Anne Rudzinski and Tim Brunet about how to plan a podcast. The UWill Discover Podcast is a University of Windsor initiative of the UWill Discover Sustainable Futures project. UWill Discover is a year-long program where University of Windsor undergraduate and graduate students share their experiences in doing creative and research work. Students can participate in: a week-long conference writing workshops a writing retreat a STEMx Policython (like a hackathon for policymaking) publishing the UWill Discover Journal The UWill Discover publications are archived through the wonderful work of the Leddy Library at Scholarship at UWindsor. Learn more about the project at the UWill Discover Sustainable Futures website!
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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 | 0.011 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.023 | 0.017 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.230 | 0.168 |
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".