Dissolved inorganic carbon, total alkalinity, pH on total scale, and other variables collected from profile and discrete sample observations using CTD, Niskin bottle, and other instruments from NOAA Ship Ronald H. Brown in the U.S. West Coast California Current System from 2016-05-08 to 2016-06-06 (NCEI Accession 0169412)
Bibliographic record
Abstract
This dataset contains the discrete carbon data collected during the 2016 West Coast Ocean Acidification (WCOA) cruise. WCOA2016 took place May 5 to June 7, 2016 aboard NOAA Ship Ronald H. Brown. It is the most integrated WCOA cruise so far, with 132 stations occupied from Baja California in Mexico to Vancouver Island in Canada along seventeen transect lines. At all stations, CTD casts were conducted, and discrete water samples were collected in Niskin bottles. The cruise was designed to obtain a synoptic snapshot of key carbon, physical, and biogeochemical parameters as they relate to ocean acidification (OA) in the coastal realm. Physical, biogeochemical, and chlorophyll concentration data collected during CTD casts are included with this data set. During the cruise, some of the same transect lines were occupied as during the 2007, 2011, 2012, and 2013 West Coast Ocean Acidification cruises, as well as CalCOFI cruises. This effort was conducted in support of the coastal monitoring and research objectives of the NOAA Ocean Acidification Program (OAP). Data Use Policy: Data from NOAA West Coast Ocean Acidification (WCOA) cruises are made freely available to the public and the scientific community in the belief that their wide dissemination will lead to greater understanding and new scientific and policy insights. The investigators sharing these data rely on the ethics and integrity of the user to ensure that the institutions and investigators involved in producing the WCOA cruise datasets receive fair credit for their work. If the data are obtained for potential use in a publication or presentation, we urge the end user to inform the investigators listed herein at the outset of the nature of this work. If these data are essential to the work, or if an important result or conclusion depends on these data, co-authorship may be appropriate. This should be discussed at an early stage in the work. We request that any manuscripts using these data be sent to all investigators listed in the metadata before they are submitted for publication so that we can ensure that the quality and limitations of the data are accurately represented. Please direct all queries about this dataset to Simone Alin and Richard Feely.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 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) | 0.007 | 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".