Bibliographic record
Abstract
The American Northern Theater Army in 1776, by Douglas R. Cubbison (316 pages, January 2010), discusses the catastrophic defeat of the Continental Army during its invasion of Canada and its remarkable reconstruction at Fort Ticonderoga in 1776 by Generals Horatio Gates and Phillip Schuyler.The recuperated, reinforced, and refortified troops managed to discourage a British invasion through Lake Champlain that year and, though Fort Ti fell a year later, set the stage for the British defeat at Saratoga and ultimate victory for the Americans.Cubbison cites a remarkable amount of original sources to support his narrative.$45.00.McFarland.978-0-7864-4564-6.American Zombie Gothic: The Rise and Fall (and Rise) of the Walking Dead in Popular Culture, by Kyle William Bishop (239 pages, January 2010), investigates the origins and characteristics of zombie cinema, focusing especially on George Romero's "Dead" series and the extraordinary fascination with the walking dead in post-9/11 America.Bishop points out that the zombie is a unique cinematic monster in that it developed from Haitian folklore, rather than European literature, making it a distinctly New World creation.Zombie films reflect viewers' fears of an unsettled afterlife, a complete breakdown in the social order, uncontrollable epidemics, terrorist attacks, and enslavement by an alien cultureelements that identify them as postmodern contributions to the Gothic literary tradition.Bishop also looks at zombie comedy films
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.675 | 0.616 |
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".