doi:10.5194/hess-19-1287-2015 © Author(s) 2015. CC Attribution 3.0 License. Reply to D. L. Peters ’ Comment on “Streamflow input
Bibliographic record
Abstract
Abstract. This paper provides a reply to a comment from Peters (2014) on our recent effort focused on evaluating changes in streamflow input to Lake Athabasca, Canada. Lake Athabasca experienced a 21.2 % decline in streamflow input between 1960 and 2010 that has led to a marked de-cline in its water levels in recent decades. A reassessment of trends in naturalized Lake Athabasca water levels shows insignificant changes from our previous findings reported in Rasouli et al. (2013), and hence our previous conclusions re-main unchanged. The reply closes with recommendations for future research to minimize uncertainties in historical assess-ments of trends in Lake Athabasca water levels and to better project its future water levels driven by climate change and anthropogenic activities in the Athabasca Lake basin. 1
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.107 | 0.069 |
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".