Transition in Residues: On Depleted Oil Wells, Radioactive Geophysics, and the Origins of the Twentieth Century's Energy Mix
Bibliographic record
Abstract
The oil and uranium industries always have been intertwined. Both industries are inherently global and span an extensive geological history. The formation of uranium and oil deposits, and their eventual extraction, is a story circling through early planetary history, continuing in depleted oil wells in Germany, Canada, and France, and lingering well into the second half of the past century. Understanding this history proved to be the key for two businesses that would shape the later twentieth century: the oil and nuclear industries. Oil companies are among the very first to integrate new quantum mechanics and knowledge about radioactive decay into their search for oil. This article locates the origins of this interconnectedness in the emergence of applied geophysics. Based on case studies to the experiments and research projects of geophysicist Richard Ambronn and the studies by the oil service company Schlumberger into measuring radioactive decay as a method of determining underground sediments and finding oil during the 1920s and 1930s, this article argues that the depleted oil sources at Pechelbronn and Celle formed the basis of both industrial and academic developments in the knowledge of radioactivity, geophysics, and petroleum.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.019 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".