Dissolved and particulate organic carbon chemistry for freshwater and marine stations from 2014 through 2016 on Calvert and Hecate Islands, British Columbia, Canada
Bibliographic record
Abstract
This data package includes three datasets used to assess spatial and temporal patterns in dissolved organic carbon (DOC) and particulate organic carbon (POC) across freshwater streams and nearshore marine stations on Calvert and Hecate Islands on British Columbia’s Central Coast, associated with St. Pierre and Oliver et al. (2020, submitted). The datasets include: ‘Compiled Freshwater - Marine Dataset - Final.xlsx’: DOC and POC concentrations and stable isotope signatures across freshwater (n = 7), marine outlet-adjacent (n = 7) and marine-mid-channel (n = 6) stations, sampled during routine twice monthly or monthly surveys conducted between January 9th 2014 and November 23rd 2016. Also includes temperature, salinity, pH data (freshwater only), and total chlorophyll a concentrations (marine only) during the surveys. ‘Rainfall Events - Final.xlsx’: DOC and POC concentrations and stable isotope signatures, temperature, pH, salinity, and microbial cell counts across the two freshwater plumes surveyed during rainfall events on August 7th 2015 and September 19th 2015. ‘PARAFAC Results with all Associated Variables.xlsx’: Results of parallel factor (PARAFAC) analyses conducted on dissolved organic matter samples collected in 2016 from both freshwater and marine stations on Calvert and Hecate Islands. Sample collection and processing information can be found at: St. Pierre, K.A., Oliver, A.A., Tank, S.E., Hunt, B.P.V., Giesbrecht, I., Kellogg, C.T.E., Jackson, J.M., Lertzman, K.P., Floyd, W.C., Korver, M.C. (2020) Terrestrial exports of dissolved and particulate organic carbon to nearshore ecosystems of the Pacific coastal temperate rainforest.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".