Bibliographic record
Abstract
This campaign, entitled Sea Ice Effect on Arctic Precipitation, started in January 2010 and ended in December 2016. The campaign involved sampling precipitation, storm by storm, within the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility observatory at Barrow, Alaska. Before the ARM Atqasuq, Alaska site was closed in September, 2014, precipitation samples were also collected at Atqasuq. The objective of this campaign was to study how sea ice retreat under warming conditions affects the arctic hydrological cycle, namely evaporation and precipitation, using oxygen and hydrogen isotopic measurements in precipitation. One of the roles of sea ice in the arctic climate system is to influence evaporative fluxes from the sea surface. When sea ice melts, the evaporation is promoted from the newly opened sea surface, which increases the moisture supply, and precipitation. Reduction of sea ice cover may feed back to the climate system in several ways. First, it affects the latent heat flux from the sea surface. Second, the increased precipitation in the Arctic may change the surface albedo. For example, if the increased precipitation falls as snow, it would increase the albedo in spring due to delayed melting. Both mechanisms would affect the radiation balance of the Arctic and thus induce additional climate change. Stable isotopic ratios in precipitation record meteorological conditions from the moisture source through the transport path and to the precipitation site. If moisture from the arctic sea surface increases, the average transport distance would decrease. This would result in an enrichment of oxygen-18 and deuterium in precipitation. Samples collected at Barrow allow us to track the moisture source areas for each sampled storm and analyze if the sea ice change is associate with systematic shift of hydrological conditions. Between July 2011 and December 2014, Barrow was one of the sites in a network of pan-Arctic precipitation observations in the project called iisPacs, standing for Isotopic Investigation of Precipitation in Sea ice in the Arctic Climate System. The project included eight stations where precipitation was collected following the protocols developed in Barrow and Atqasuq. These stations included Barrow and Atqasuq, Alaska, Cambridge Bay, Canada, Ny Ålesund, Norway, Ikerasaarsuk and Summit, Greenland, and Chersky and Tiksi, Russia. Currently, synthesizing data from all of these stations is in progress.
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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 | 0.001 |
| 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) | 0.004 | 0.002 |
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".