Bibliographic record
Abstract
This is a systematic analysis of components of delivered fuel prices in Alaska. Data for the analysis include limited publicly available Alaska fuel prices (fall 2007 prices), as well as information the authors gathered from extensive interviews with fuel retailers and transporters, communities, and agencies. We identify the individual components of delivered fuel costs—including world price of crude oil, refining costs, transportation costs, storage and distribution costs, taxes and financing costs—and investigate how these factors influence the final retail prices of home heating fuel and gasoline. Transportation, storage, and distribution costs appear to be the most variable factors driving the large retail fuel price differentials among Alaska communities. Therefore, we investigate how factors such as seasonal icing, the number of fuel transfers enroute to specific communities, local storage and delivery infrastructure, marine and river characteristics, and distance from refineries or fuel hubs influence fuel prices. We did an in-depth analysis of how those factors influence prices in ten case study communities around the state—Allakaket/Alatna, Angoon, Bethel, Chitina, False Pass, Fort Yukon,
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.537 | 0.292 |
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".