Bibliographic record
Abstract
WKU's alumni magazine. Contents: Ransdell, Gary. President’s Letter Record Number of WKU Students, Recent Graduates Earn National Scholarships First Cohort Begins WKU’s Doctor of Physical Therapy Program Gatton Academy of Mathematics & Science Named America’s Top High School for 2nd Year in Row David Porter Elected Board of Regents Chair Regents Approve Budget, Tuition WKU Forensics Team Wins National Forensics Association Championship Faculty Member Awarded National Academy of Education Fellowship Grant – Jie Zhang WKU President Joins Institute for Shipboard Education Board – Gary Ransdell WKU Storm Chasers Document EF-4 Tornado, Other Severe Weather Events Paul & Ellen Schuhmann Student Publications Scholarship Fund Scholarship Spotlight – Sam Oldenburg Greenwood Optimist Club Closes But Scholarship Keeps Legacy Alive Niedermeier, Lynn. Ghost Hunting at WKU West, Natalie. Horse Wrangler: Rusty Hendrickson Minton, Lynn. It’s Cool to Be a Farmer Again Niedermeier, Lynn. Birth of a Tradition: The First Homecoming Bright Lights Red City – Homecoming Three to Join WKU’s Hall of Distinguished Alumni – Dan Cherry, John Minton Jr., Greg Smith Biggs, Stacy. International Reach – China Smith, Jennifer. Capitol Spotlight: Dorsey Ridley Vickery, Amanda. WKU-Glasgow Reaches Further Adventures of the Red Towel In Memoriam Class Notes
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.814 | 0.727 |
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".