Fort Yukon wood Energy Program Wood Boiler Deployment (Final Report)
Bibliographic record
Abstract
The Fort Yukon Gwitchyaa Zhee Corporation (GZ) worked with partners on the development of an Integrated Biomass Energy Program for Fort Yukon. This integrated approach linked sustainable forest management with an in- village for -profit wood harvest and delivery business to displace diesel energy with wood energy for heat and power. The program was based on the concept of ecological, economic and social sustainability with a goal of displacing as much diesel and fuel oil as is technically feasible and sustainable; essentially systematically converting a village to significant amounts of wood use. Additionally, GZ worked with the Alaska Energy Authority (AEA) on the development of a rural power system upgrade (RPSU) project that replaced GZ’s existing antiquated diesel power plant and provided upgrades to the existing electrical distribution system. Due to the synergy of the two projects, the Biomass and RPSU projects were combined to provide improved operating efficiency, economy of scale and increased benefits to GZ, the Council of Athabascan Tribal Governments (CATG) and the community of Fort Yukon. The combined project is referred to as the Fort Yukon Combined heat and power (CHP) project. The purpose of the DOE Tribal Energy Program award was to support the preconstruction tasks and installation of wood boilers at the CATG clinic, and at the new GZ diesel power plant as part of an overall program to create a for- profit wood energy utility in Native Village of Fort Yukon. The CHP project provides biomass and diesel generation recovered heat via a new district heating system to the major commercial buildings in Fort Yukon. The CATG clinic will receive heat from a separate biomass boiler to their heating needs. The award from the Department of Energy (DOE) Tribal Energy Program was divided into two phases: Design/Permitting (phase 1) and Construction (phase 2). Phase 1 (Design & Permitting) is cost shared using State of Alaska Renewable Energy Funding (REF) funds through the Alaska Energy Authority (AEA). Phase 2 (Construction) was funded by DOE, AEA and US Department of Agriculture Rural Utility Service (USDA-RUS). Phase 1 of this grant, along with a separate grant from the Denali Commission provided funding for development of the wood delivery infrastructure necessary to support the CHP project. Under phase 2, This DOE grant supported final design of the boiler, bidding, purchase and transport of boilers, installation, technical support and engineering. The AEA and RUS grants supported permitting, final design, material and equipment purchase, and construction and installation of the new diesel power plant and district heating distribution system.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
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".