Bibliographic record
Abstract
Deseo escribir brevemente, con admiracion y gratitud, sobre mi amigo Larry, de 90 anos, un profesor universitario que influyo mucho en el rumbo de mi carrera y al que visite con mi familia hace unos meses durante el verano del hemisferio norte, en su acogedora casa, en el suburbio de Charlotte, en el estado de Vermont, EEUU, vecino a la provincia de Quebec, Canada. Larry sigue siendo un forestal inquieto, con una vitalidad envidiable. Hace unos pocos anos protestaba con un grupo de activistas en Washington DC frente a la Casa Blanca, por la preservacion de unas montanas amenazadas por un oleoducto promovido por el gobierno del presidente Obama. Actualmente es uno de los encargados de velar por el buen estado de los arboles de su comunidad (Town Tree Warden) y esta comprometido en la restauracion de los arboles plantados a lo largo de los caminos de Charlotte. Larry y su esposa Linda inspiran ejemplos de lo mucho que la gente jubilada puede hacer y lo que es una vida dedicada a una causa en la uno cree firmemente.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.056 |
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; both teacher heads 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".