Strengthening connections across disciplines and borders through an international permafrost coastal systems network (PerCS-Net)
Bibliographic record
Abstract
Changes in the Arctic system have increased the vulnerability of permafrost coasts to erosion and altered coastal morphologies, ecosystems, biogeochemical cycling, infrastructure, cultural and heritage sites, community well-being, and human subsistence lifestyles. Better understanding the pace and nature of rapid changes occurring along permafrost coastlines is urgent, since a high proportion of Arctic residents live on or near coastlines, and many derive their livelihood from terrestrial and nearshore marine resources The US National Science Foundation’s AccelNet and Arctic System Sciences Programs, recently awarded a collaborative grant funding the Permafrost Coastal Systems Network (PerCS-Net). PerCS-Net focuses on leveraging resources from existing national and international networks that have a common vision of better understanding permafrost coastal system dynamics and emerging transdisciplinary science, engineering, and societal issues in order to amplify the broader impacts by each individual network. PerCS-Net strengthens linkages between existing networks based in Germany, Russia, Norway, Denmark, Poland, and Canada with the activities of several active US NSF-funded networks as well as several local, state, and federally funded US-based networks. PerCS-Net will benefit the US and international research communities by (1) developing internationally recognized protocols for quantifying the multitude of changes and impacts occurring in Arctic coastal permafrost systems, (2) sustaining long-term observations from representative coastal key sites, (3) unifying annual and decadal-scale observations of circum-arctic permafrost-influenced coasts, (4) refining a circum-arctic coastal mapping classification system and web-based delivery of geospatial information for management planning purposes and readily accessible information exchange for vulnerability assessments, (5) engaging local communities and observers to capture impacts on subsistence and traditional livelihoods, and (6) promoting synergy across networks to foster the next generation of students, postdoctoral scholars, and early-career researchers faced with the known and unknown challenges of the future Arctic System. Ultimately, PerCS-Net will develop a circumpolar alliance for Arctic coastal community information exchange between stake-, rights- and knowledge holders, scientists, and land managers. There is increasingly diverse interest in permafrost coastal system issues and currently no unified source of information on the past, present, and potential future state of permafrost coastal systems that provide the level of detail needed to make decisions at scales relevant for indigenous communities across the Arctic. Such new engagement will inform intergovernmental agencies and international research and outreach programs in making science-based decisions and policies to adapt to changing permafrost coastal system dynamics. PerCS-Net will build a network of networks to assess risks posed by permafrost coastal system changes to local and global economies and well-being and facilitate knowledge transfer that will lead to circum-arctic adaptation strategies.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.064 | 0.012 |
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".