Bibliographic record
Abstract
Seventy-nine years ago, Elsie MacGill was on the exciting verge of becoming the first woman from Canada to receive a bachelor's degree in electrical engineering, when, after experiencing flu-like symptoms for a few days, she woke up one morning to discover that she was completely paralyzed from the waist down.1 She was eventually diagnosed with acute infectious myelitis and was told she would never walk again. We have heard those words before. In 1929, times were tough enough for a woman who wanted to become an engineer … the addition of a disability such as this would seem to be too much to overcome. Well, MacGill finished her university tests from her hospital bed and received her degree. She was determined to not be bedridden and eventually used canes for mobility. During her recovery, while writing a magazine article titled Women on the Wing, she learned that it took very little strength to pilot a plane, and she developed an interest in aeronautics. She ended up pursuing further study at MIT and became a well-respected aircraft designer during the Second World War.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.599 | 0.397 |
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".