The Forgotten Coast: A Synthesis of Current Knowledge of Southern Chukchi Sea Lagoon Ecosystems
Bibliographic record
Abstract
In the Southern Chukchi Sea Region (SCSR) of the Alaskan Arctic, approximately 40% of the coastline consists of freshwater-brackish lagoons and the gravel spits that separate them from the ocean. These lagoons are important rearing, feeding, and spawning habitats for diverse fish and invertebrate assemblages composed of freshwater, diadromous, and marine taxa. Many of these species are prey for a suite of marine mammals and avian predators in addition to being important to the food security of subsistence users from the surrounding region. Despite recognition of the ecological and cultural importance of these habitats from as far back as the 1950s, the body of knowledge surrounding lagoons of the SCSR contains many knowledge gaps and fails to comprehensively capture the dynamic nature of both biotic and abiotic factors that define the functional ecology of these habitats. This report synthesizes the available knowledge of SCSR lagoons, including geomorphology, hydrology, food web structure, and local knowledge. We also recommend avenues of future study, such as characterizing the basal trophic levels of lagoon food webs. Only by constructing a more detailed and comprehensive knowledge base of SCSR lagoon ecology will management and conservation efforts in the region be able to address and mitigate potential threats resulting from expanding infrastructure and global climate change, while simultaneously supporting the diverse portfolio of lagoon habitats that have a vital role in regional subsistence practices and food security.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".