Turkey Lakes Watershed - Stream Water Chemistry
Bibliographic record
Abstract
This dataset contains average concentrations of water chemistry collected from 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. These are average concentrations recorded from 1981-2018 in milligrams per litre (mg/L) of major ions (Ca, Mg, K, Na, SO4, Cl, NO3-N, NH4-N) and some nutrients (TP, TN) collected by the Great Lakes Forestry Centre. Samples are collected according to variable schedules such that frequency generally increased with increasing stream flow, (sampling period was shortest during spring runoff, 1-3 days, and longest during winter, 2-3 weeks). Sampling was accomplished by rinsing an appropriately cleaned 2-litre, polyethylene bottle at least 3 times with stream water followed by immersion to collect the final sample. Care was taken to not disturb the stream sediments throughout the sampling procedure. pH and conductivity testing is completed right after sampling. Other chemical analyses are completed by the Great Lakes Forestry Centre in Sault Ste. Marie within 2 weeks of collection. Sample integrity was maintained through storage in the dark at 4 degrees Celsius and analyzed at room temperature.
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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 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.017 |
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".