Industrial legacies in a rapidly changing Arctic
Bibliographic record
Abstract
Database and source codes used to investigate the impact of permafrost thaw on industrial legacies in the Arctic: The file Industrial_Sites.zip includes geospatial data (point shape file) on the location of industrial sites above 55°N. The data synergizes data from OpenStreetMap (OSM) and the Nordregio Atlas of population, society and economy in the Arctic from 2019. The file Contaminated_Sites_Program_Alaska.zip includes geospatial data extracted from the database of the Contaminated Sites Program in Alaska. The data set contains location, associated industrial sector, first date of registration, and associated chemical substances. The file Contaminated_Sites_Canada.zip includes geospatial data extracted from the database of the Federal Contaminated Sites Inventory (FCSI) of Canada. The data set contains besides location and the local permafrost probability, additional information on contamination type and the treatment status. The file Contaminated_Sites_Russia.zip contains geodata about industrial contamination events in Russia. The dataset was created based on a Google search using keywords in Russian ("загрязнение" - pollution; "разлив нефтепродуктов" - oil spill; "техногенная авария" - industrial accident or disaster; "Арктика" - Arctic; "мерзлота" - permafrost) and a search of several online media (including local and federal news portals). The database includes the locations of contamination events, the date, and information about the type of event, as well as the link to the media source. In some cases, the contaminated area and volume of the spill are also provided. The file Point_Process_Modeling.zip contains geospatial data of industrial sites and contaminated sites in Alaska and Canada and an R script used to fit two point process models to the data. The results deliver intensity maps of contaminated sites in the Arctic permafrost region. The file PanArctic_Simulations.zip includes the source code of the CryoGrid permafrost model (Julia Language v. 0.6.4) and a start script with all parameters and forcing data (JSON) required to run the model for industrial sites located in the Arctic permafrost region. The file Analysis_Industrial_Contaminated_Sites_Arctic.zip contains data and scripts to analyze permafrost degradation at industrial sites and contaminated sites in the Arctic following the simulations performed with PanArctic_Simulations.zip and the site locations contained in Industrial_Sites.zip and the intensity map derived by Point_Process_Modelling.zip. The file Geospatial_DataCollection.zip contains the complete database used to analyze and visualize the occurences of industrial contaminations in the Arctic. The file Visualization_Geospatial_DataCollection.zip contains a collection of additional python scripts used to plot data and analysis results contained in Geospatial_DataCollection.zip. Please note that all paths pointing to the datasets used in the scripts have to be changed accordingly.
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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 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".