Bibliographic record
Abstract
I currently serve as the Interim Director of Integrated Student Services (ERNIE Central). I have been employed at Embry-Riddle Aeronautical University for 13 years. I got my start in the Financial Aid office. I proudly served for 7 years in the United States Air Force as a Nuclear Weapons Specialist. As a Sergeant I worked as a Crew Chief to maintain and replace limited life components on our munitions. I attended basic training at Lackland AFB in San Antonio, Texas. I went from there to Lowry AFB in Denver Colorado for my Technical School. My first duty station was Barksdale AFB in Bossier City, LA where I spent 3 years maintaining the munitions that were aging out of the inventory. From there I went to Ghedi AFB in Ghedi, Italy. This was an Italian AFB. The Italian Air Force flew the planes and we provided the munitions. I ended my career at Fairchild AFB in Spokane Washington. I was a marksman Earned NCO of the quarter my first board Was recognized for recommending a change to the design and hardware for bomb racks that not only made the rack more reliable but saved money in hardware and time for repair.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.485 | 0.219 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".