Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Heavy Metal: Earth’s Minerals and the Future of Sustainable Societies brings together world-leading experts from across the globe to reimagine the future of mineral exploration and mining in a post-fossil fuel world. Minerals and metals – for batteries, circuit boards, wiring and other components – are essential to a digital, carbon-neutral economy. But how can we grapple with the environmental, social and geopolitical challenges caused by the extraction and use of these critical resources? Concise, accessible, and engaging, the essays in this timely collection intertwine a broad spectrum of disciplines to help us understand and reimagine our relationship with minerals. Exploring a wide range of themes, from the colonial history of mining and Indigenous resistance, to new frontiers in exploration geology, waste management and recycling, this book draws on experts from fields as diverse as geology, mining engineering, law, economics and public policy. The book also explores mineral resources through an artistic lens, with a collection of stunning images from the Canadian photographer Edward Burtynsky, and excerpts of a new musical work, the Heavy Metal Suite. This thought-provoking and ultimately hopeful book guides us towards a more responsible, ethical and sustainable use of metals and minerals. It is essential reading for anyone interested in how we supply the resources needed for a carbon-neutral economic future.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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 it