Geological Knowledge: A Key to the Future of the Diamond Industry
Bibliographic record
Abstract
The geological knowledge needed to find diamond deposits has increased substantially since the early 1950s and is now readily available in the public domain. This has resulted in the discovery of many new diamond deposits in the last 50 years and, therefore, an oversupply of rough diamonds at various times. Based on analogies with other mineral commodities, new diamond deposits will be found at an accelerated rate as diamond-related geological knowledge continues to expand and exploration methods are refined. In such circumstances, as with all commodities, in the long term (>20 years) new markets must be found to keep pace with increased production, otherwise there may be an ever-present concern based on oversupply. Resume La somme des connaissances geologiques requises en vue de decouvrir des gise-ments de diamants s'est considerablement accrue depuis le debut des annees 50 et, ces connaissances ayant ete largement diffusees depuis, chacun peut maintenant y acceder. En consequence, depuis les derniers 50 ans, un grand nombre de gisements de diamants ont ete decouverts, a tel point que par moments, il y a eu surplus de l'offre de diamants bruts. Comme pour tout autre matiere premiere minerale le nombre de nouvelles decouvertes diamantiferes ira s'accelerant au fur et a mesure de l'acquisition de nouvelles connaissances geologiques et du raffine-ment des methodes d'exploration. Et, comme pour toute matiere premiere, il faudra a terme (20 ans et plus) decouvrir de nouveaux marches sans quoi, l'indus-trie sera constamment au prise avec un probleme de surplus.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".