Bibliographic record
Abstract
Lanka's trade ministry approached the Chinese government for investment in its mining and mineral processing sectors, with particular emphasis on mineral sands and graphite. Rishad Bathiudeen, Lanka's Minister for trade and commerce, was quoted as telling China's envoy to Colombo, Wu Jianghao, during a visit to the island in March that Sri Lanka wants to upgrade its mineral sector, and that it was looking to Asia's biggest economy to back its development initiatives. One of Canada's leading graphite exploration companies, Mason Graphite Inc, joined only a handful of juniors in publishing production and cost details of its Lac Guret project in north Quebec. Using IM's graphite prices as the basis for its preliminary economic assessment (PEA), Mason expects to produce a tonne of flake graphite concentrate for $390/tonne which, if realised, puts it in line with the higher-cost Chinese producers. Swiss graphite producer Timcal SA, part of Imerys, has confirmed that it is seriously considering graphene as a market for its graphite products Graphene production is one potential route for natural graphite, as well as synthetic carbon, and this is interesting to us, Dr Sergio Pacheco Benito, development scientist for Timcal, told IM at the ImagineNano Graphene 2013 meeting in Bilbao.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".