Bibliographic record
Abstract
In early April 2015, some frac sand companies were beginning to feel the pinch. Superior Silica Sand, a wholly-owned subsidiary of Emerge Energy Services, announced on 7 April that it had cancelled plans for a new Wisconsin-based frac sand processing facility as a result of tough market conditions. company's CEO, Rick Shearer, said that this was a difficult but necessary decision that was made owing to the project being no longer economically viable. Rick Shearer, CEO of frac sand supplier Superior Silica Sands, explained in January 2015 to the Cap City Times that, We certainly expect things will be softer in 2015 than they were in 2014. But he added that, The good news is that those who are still drilling are using more sand per well. CEO of US Silica shares this perspective. * Fracking bans : in December 2014, the first ban on new fracking came into effect in the city of Denton, Texas; Governor Andrew Cuomo announced that fracking would be banned in New York state; and in Canada, the New Brunswick government was discussing a moratorium on fracking unless five specific conditions are met. Further, in 2015, Houston County discussed a frac sand mining ban; Litchfield County town, Washington, proposed the state's first fracking ban; and the Maryland House of Delegates approved a three-year fracking moratorium. On the contrary, Ontario rejected a fracking moratorium on 26 March 2015
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) | 0.001 | 0.001 |
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".