Turkey Lakes Watershed - Stream Water Flow
Bibliographic record
Abstract
This dataset contains annual mean stream water flow/discharge data derived from daily means for headwater streams draining forested hillslopes measured at stream catchments C31, C32, C33, C34, C35, C37, C38, C39, C42, C46, C47, C49, and C50 in the Turkey Lakes Watershed, approximately 60 km northwest of Sault Ste. Marie, Ontario, Canada. This data set is recorded as annual mean flow by calendar year (January-December in litres per second), annual mean flow by water year (October to September in litres per second), and annual number of zero flow days by water year. Daily mean flows that were used to derive this data set were recorded from 1981-2012 by the Great Lakes Forestry Centre, and are reported for 1981-2011 due to some inaccuracies throughout the 2012 data. Hydrological gauging stations employ "flow-control" 120 degree V-notch weirs (catchments 31, 33, 34, 37, 39, 42, 46, and 47), 90 degree V-notch weirs (catchments 32, 35, and 49), and 60 degrees V-notch weirs (catchment 38) to facilitate monitoring of stream discharge. Water "stage" or depth within the structure (e.g. in the pool behind the weir notch) is automatically and continuously recorded by chart recorders (Leupold & Stevens A-71 SE Water Level Recorder) from 1981-2003. Capacitance rods (Trutrack WT-HR 1000) installed in stilling wells replaced the chart recorders over the period of 2002 to 2003 and were used until 2012. The capacitance rods logged data at 1 hour intervals for the majority of their use and then averaged to a daily rate. Manual stage measurements have been taken intermittently when synoptic water chemistry samples were taken throughout the years. Stage data are then converted to a continuous record of flow using the relationship between stage and discharge measurements.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.016 |
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".