Discrete water samples collected from the Conductivity-Temperature-Depth rosette at specific depths, CCGS Sir Wilfrid Laurier, Northern Bering Sea to Chukchi Sea, 2019
Bibliographic record
Abstract
The Pacific sector of the Arctic Ocean is experiencing major reductions in seasonal sea ice extent and increases in sea surface temperatures. One of the key uncertainties in this region is how the marine ecosystem will respond to seasonal shifts in the timing of spring sea ice retreat and/or delays in fall sea ice formation. Variations in upper ocean water hydrography, planktonic production, pelagic-benthic coupling and sediment carbon cycling are all influenced by sea ice and temperature change. To more systematically track the broad biological response to sea ice retreat and associated environmental change, an international consortium of scientists have developed a coordinated Distributed Biological Observatory(DBO) that includes selected biological measurements at multiple trophic levels, along with satellite and mooring measurements. The DBO currently focuses on five regional biological "hotspot" locations along a latitudinal gradient that allows for consistent sampling and monitoring at five biologically productive locations across a latitudinal gradient: DBO 1 (SLIP)-south of St. Lawrence Island (SLI), DBO2 (Chirikov)-north of SLI, DBO3 (southern Chukchi Sea), DBO4-NE Chukchi Sea,and DBO5-Barrow Canyon.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.014 |
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".