Biogeochemical Sampling of Streams in the Kwakshua Watersheds of Calvert and Hecate Islands, BC: 2013-2019
Bibliographic record
Abstract
This dataset contains the analytical results of freshwater biogeochemical samples collected on Calvert and Hecate Islands on the central coast of British Columbia, Canada, from April 2013 to December 2019. Samples were collected, approximately monthly, year round at the stream outlets of the seven largest watersheds, which are gauged as part of the Kwakshua Watersheds Observatory. The samples were analyzed for dissolved organic carbon (DOC) concentration and stable isotopes, particulate organic carbon and nitrogen (POC and PON) concentration and isotopes, dissolved organic matter (DOM) composition (via metrics of absorbance and fluorescence), total, dissolved, and inorganic nutrients, metals and major ions, water isotopes, and total suspended solids (TSS). Complimenting each water chemistry sample, we measured electrical conductivity, temperature, pH, oxidation reduction potential (ORP), and dissolved oxygen in-situ with a hand-held sensor. General field methods From the Calvert Island field station, each stream was accessed by a short boat ride (~10 min). The field team was dropped on land and walked up-stream to the pre-established sampling location, above tidal influence. For most sample types, water was filtered streamside, using a 0.45 µm filter attached to a syringe. POC, PON, and TSS samples, however, were brought back to the laboratory, to be filtered via vacuum filtration, using a grade GF/F 0.7 µm filter. The samples were then preserved, according to the Hakai preservation protocol before being sent to external analytical laboratories for analysis. The absorbance and fluorescence samples as well as TSS samples were analyzed on site by Hakai technicians. The resulting data were reviewed and flagged following our standard quality control (QC) procedures. This data package contains the quality controlled data as well as detailed documentation of the methods used to collect, analyze, and QC the data.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".