Bibliographic record
Abstract
A finales del mes de agosto del ano 1896, un hombre excitado irrumpia en el saloon de Bill McPhee en la pequena poblacion de Fortymile, un campamento minero en la riba del rio Yukon, en Canada. El pueblo no tenia ni diez anos desde su creacion y se habia establecido junto a un pequeno yacimiento de oro que habia atraido a muchos mineros pero cuyas minas habian resultado pobres. Muchos de esos mineros desanimados pasaban las horas entre botellas de whisky y juegos de cartas. Cuando el forastero entro con las ropas sucias y arrugadas de unos dias de viaje, los cabellos revueltos, una barba descuidada y una mirada intensa, todos se giraron sorprendidos. El hombre, con la respiracion entrecortada por la emocion, dijo solo unas palabras: —Chicos, ihemos encontrado oro rio arriba! Esas palabras pronunciadas por George Carmack (figura 1) fueron el detonante de la mayor fiebre del oro de la historia, la fiebre del Klondike. El 17 de agosto de ese ano, George Carmack, Skookum Jim (figura 2) y Tagish Charlie habian encontrado oro en el lecho de Bonanza Creek, un afluente del rio Klondike, cerca de donde este desemboca en el Yukon.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".