Arctic Great Rivers Observatory I Biogeochemistry Data (2009 - 2011)
Bibliographic record
Abstract
The PARTNERS and Arctic-GRO projects sample the biogeochemistry of the six largest rivers draining to the Arctic Ocean. To the greatest extent possible, sample collection techniques are identical across rivers. Once collected, samples are returned to Woods Hole, MA, from where they are shipped to expert laboratories for analyses. The Arctic Great Rivers Observatory I (Arctic-GRO I) Project was the successor to PARTNERS. Arctic GRO I spanned the years between 2009 and 2011, with sampling that followed the approach used during PARTNERS. On each river, samples were collected five times per year: three during the freshet, one during late summer, and one under ice. In addition to this "comprehensive" collection of data five times per year, samples were also collected daily during the freshet and analyzed for a subset of constituents. The daily freshet samples were collected from directly beneath the water surface using a polycarbonate collection bottle. The Arctic Great Rivers Observatory II (Arctic-GRO II) Project (2012-2016) follows Arctic GRO I. Full field and laboratory details for Arctic GRO I can be found in the "Sample Collection and Analyses" document on this page.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.024 |
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".