Bibliographic record
Abstract
Abstract Folk explanations of notable geological features, including fossils, are found around the world. Observations of fossil exposures (bones, footprints, etc.) led to place names for rivers, mountains, valleys, mounds, caves, springs, tracks, and other geological and palaeontological sites. Some names describe prehistoric remains and/or refer to traditional interpretations of fossils. This paper presents case studies of fossil-related place names in ancient and modern Europe and China, and Native American examples in Canada, the United States, and Mexico. Evidence for the earliest known fossil-related place names comes from ancient Greco-Roman and Chinese literature. The earliest documented fossil-related place name in the New World was preserved in a written text by the Spanish in the sixteenth century. In many instances, fossil geonames are purely descriptive; in others, however, the mythology about a specific fossil locality survives along with the name: in still other cases the geomythology is suggested by recorded traditions about similar palaeontological phenomena. The antiquity and continuity of some fossil-related place names shows that people had observed and speculated about mineralized traces of extinct life forms long before modern scientific investigations. Traditional place names can reveal heretofore unknown geomyths as well as new geologically-important sites.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".