Hualapai Wind Project Feasibility Report
Bibliographic record
Abstract
The Hualapai Department of Planning and Economic Development, with funding assistance from the U.S. Department of Energy, Tribal Energy Program, with the aid of six consultants has completed the four key prerequisites as follows: 1. Identify the site area for development and its suitability for construction. 2. Determine the wind resource potential for the identified site area. 3. Determine the electrical transmission and interconnection feasibility to get the electrical power produced to the marketplace. 4. Complete an initial permitting and environmental assessment to determine the feasibility for getting the project permitted. Those studies indicated a suitable wind resource and favorable conditions for permitting and construction. The permitting and environmental study did not reveal any fatal flaws. A review of the best power sale opportunities indicate southern California has the highest potential for obtaining a PPA that may make the project viable. Based on these results, the recommendation is for the Hualapai Tribal Nation to move forward with attracting a qualified wind developer to work with the Tribe to move the project into the second phase - determining the reality factors for developing a wind project. a qualified developer will bid to a utility or negotiate a PPA to make the project viable for financing.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.042 | 0.008 |
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 source (direct Gemma or distilled Codex), 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".