The origin of pine pollen grains captured from air at Calypsobyen, Svalbard
Bibliographic record
Abstract
Spitsbergen is the largest island in the Svalbard Archipelago (Norway) that has been permanently populated. The harsh Arctic climate prevents development of large vascular plants such as trees. A two-year aerobiological survey was conducted within the framework of two consecutive polar expeditions (2014 and 2015) in Spitsbergen (Calypsobyen, Bellsund). The air quality was measured continuously from June/July to August using a 7-day volumetric air sampler, Tauber trap and moss specimens. Collected air samples and gravimetric pollen deposits were processed following transfer to sterile laboratory conditions and analyzed with the aid of light microscopy. Days when pine pollen grains were detected in the air were selected for further analysis. Clusters of back-trajectories, computed using the Hybrid Single Particle Lagrangian Integrated Trajectory model in combination with ArcGIS software as well as the Flextra trajectory model, showed the movement of air masses to the sampling location at Hornsund, and thus indicated the likely origin of pollen grains. The GlobCover 2009 and CORINE Land Cover 2012 datasets were employed to establish the distribution of coniferous forests in the areas of interest. Conclusions were drawn based on the analyses of the circulation of air masses, using visualization of global weather conditions forecast to supercomputers. For the first time we have demonstrated that pine pollen grains occurring in pine-free Spitsbergen, could originate from numerous locations, including Scandinavia, Iceland, Siberia and northern Canada. Pollen grains were transported via air masses for distances exceeding ~2000 km. Both air samples and gravimetric pollen deposits revealed the same pattern of Pinus pollen distribution.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".