Selected Industrial Minerals Trends in British Columbia, 2006
Bibliographic record
Abstract
Brit ish Co lum bia has sig nif i cant po ten tial and op por-tu nity for new in dus trial min er als ex plo ra tion and de vel op-ment. In dus trial min er als are less vul ner a ble than met als to abrupt com mod ity price swings re lated to global eco nomic cy cles. Nev er the less, such cy cles do in flu ence sup ply and de mand for in dus trial min er als, in clud ing con struc tion ma-te ri als. The fol low ing dis cus sion high lights some as pects rel e vant to suc cess ful de vel op ment of in dus trial min er als de pos its in the prov ince. BC’s in fra struc ture, its in dus trial min er als en dow ment, ex plo ra tion and de vel op ment trends, and ini tia tives, which could ben e fit de vel op ers, are reviewed, as well as current production levels and new development opportunities. De ci sions re gard ing coal-fired elec tri cal gen er a tion and pos si ble new de vel op ments sur round ing off shore oil and gas re sources may have im por tant ef fects on the prov-ince’s in dus trial minerals markets. INFRASTRUCTURE In dus trial min er als are an in creas ingly sig nif i cant com po nent of in ter na tional trade. BC is stra te gi cally lo-cated on the west coast of North Amer ica (Fig 1) with easy ac cess, par tic u larly to Pa cific Rim coun tries. It has a wellde vel oped trans por ta tion and in dus trial in fra struc ture in the south ern third of the prov ince, where pop u la tion and in-dus try are con cen trated. It has sev eral deep water ports and well-main tained all-weather high way sys tems that per mit ef fi cient, long-dis tance truck ing. Rail lines link BC’s in-dus trial cen tres to ter mi nal points across Can ada and the United States. The prov ince has a sig nif i cant and underdeveloped industrial minerals potential.
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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) | 0.007 | 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".