Bibliographic record
Abstract
Abstract Chicle is a thick and odorless natural latex that comes from the Chicozapote tree (Manilkara sapota), which is indigenous in Mexico and Central America. When the sapodilla tree is cut into with a blade or infested with insects, it produces latex as a protective response. The ancient Maya and Aztec used this latex as chewing gum, a habit that Mexican president General Antonio López de Santa Anna continued in the 19th century. While in the United States, he introduced chicle to US inventor Thomas Adams, Sr., who in the 1870s produced the first mass-produced chicle chewing gum. However, it was William Wrigley, Jr. who in the 1890s entered a highly competitive gum market and innovated new marketing campaigns that appealed to a broad audience. These advertisements often proclaimed the benefits of gum chewing for digestion, dental hygiene, and the ability to improve mental focus. Wrigley used these qualities to encourage the US military to adopt chewing gum into rations starting in World War I. As military personnel shared chewing gum with children in war zones, this “American habit” spread around the world. Public officials complained about the expense of cleaning up gum-littered sidewalks, the Women’s Temperance Union even argued that chewing gum was a slippery slope that could lead to smoking, gambling, or drinking, and many cultures have strong social norms regarding gum chewing in public. Despite these challenges, William Wrigley spent millions of dollars promoting a favorable image for gum and the habit of gum chewing, and other marketers launched collectables such as baseball cards to encourage sales. Chicle-based chewing gum ultimately became a victim of its own popularity, and while researchers sought out other sources of latex, such as jelutong, balata, and gutta-percha, US manufacturers ultimately resorted to synthetic substitutes. Although the chewing gum industry of today is dominated by the use of a synthetic gum chewing base, it is worth more than $25 billion annually.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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".