Water column CO2 system measurements from Hakai Oceanographic station QU39 from January 2016 to December 2017 in northern Salish Sea, British Columbia, Canada
Bibliographic record
Abstract
pCO2 and TCO2 measurements were made on seawater collected from 12 depths at the Hakai oceanographic station QU39 in the northern Salish Sea approximately every two weeks from January 2016 to December 2017. Temperature, salinity, and pressure data were also captured using CTD profilers (either Sea-Bird Electronics or RBR units following best practices) at the time of seawater collection, and profile data was extracted for the depth at which Niskin bottles were tripped. Niskin bottle depth was determined by calibrated line meter on the research vessel and verified occasionally using RBR Solo pressure sensors. Temperature was also determined at the time of fixing the seawater samples with mercuric chloride aboard the Hakai research vessel using NIST traceable thermometers (VWR PN 23609-176). Finally, temperature and salinity were determined at the time of sample analysis at the Quadra Island Field Station (QIFS) using NIST traceable thermometers and a YSI MultiLab 4010-1 with a MultiLab IDS 4310 conductivity and temperature probe. The YSI probe was calibrated using certified reference materials of known salinity prior to seawater sample analysis. For detailed protocols on sample collection, data processing including CO2 system determination, and quality assurance, please see Pocock et al. (2017; http://dx.doi.org/10.21966/1.521066). Note alkalinity (Alk) here is assumed here to consist of carbonate, bicarbonate, borate, hydroxide, and hydrogen ions; neglecting the influence of nutrients and organic acids. The effort to collect these data are part of the Hakai Institute’s directive to advance the understanding of carbon cycling in northeast Pacific coastal settings with specific emphasis on ocean acidification.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 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) | 0.005 | 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".