Alaska Subsistence Salmon Fisheries 2005 Annual Report
Bibliographic record
Abstract
xi CHAPTER 1: INTRODUCTION 1 CHAPTER 2: OVERVIEW OF SUBSISTENCE FISHERIES IN ALASKA 7 SubSiStence HarveStS in rural alaSka 7 Subsistence Salmon Harvests in 2006 7 Statewide Subsistence Salmon Harvests, 1994–2006 8 CHAPTER 3: NORTHWEST ALASKA 23 norton Sound–Port clarence area Salmon 23 Background 23 Regulations 23 Subsistence Salmon Harvest Collection Methods 24 Norton Sound Subdistricts 1, 2, and 3: Fishing Permits 24 Port Clarence District: Salmon Lake and Pilgrim River Fishing Permits 25 Household Surveys 25 2006 Subsistence Salmon Harvests 25 Norton Sound District Subsistence Salmon Harvest 25 Port Clarence District Subsistence Salmon Harvest 26 kotzebue area Salmon 26 Background 26 Regulations 26 Harvests 26 kotzebue area SHeefiSH, WHitefiSH, and arctic cHar/dolly varden 27 CHAPTER 4: YUKON AREA 35 background 35 regulationS 35 SubSiStence HarveSt aSSeSSment metHodS 38 SubSiStence Salmon HarveStS in 2006 39 CHAPTER 5: KUSKOKWIM AREA 51 background 51 regulationS 51 Subsistence Salmon Fishing Schedule 52 Subsistence Closures during the Commercial Fishery 52
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.085 | 0.038 |
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".