The MAREDAT global database of high performance liquid chromatography marine pigment measurements
Why this work is in the frame
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Bibliographic record
Abstract
Abstract. A global pigment database consisting of 35 634 pigment suites measured by high performance liquid chromatography was assembled in support of the MARine Ecosytem DATa (MAREDAT) initiative. These data originate from 136 field surveys within the global ocean, were solicited from investigators and databases, compiled, and then quality controlled. Nearly one quarter of the data originates from the Laboratoire d'Océanographie de Villefranche (LOV), with an additional 17% and 19% stemming from the US JGOFS and LTER programs, respectively. The MAREDAT pigment database provides high quality measurements of the major taxonomic pigments including chlorophylls a and b, 19'-butanoyloxyfucoxanthin, 19'-hexanoyloxyfucoxanthin, alloxanthin, divinyl chlorophyll a, fucoxanthin, lutein, peridinin, prasinoxanthin, violaxanthin and zeaxanthin, which may be used in varying combinations to estimate phytoplankton community composition. Quality control measures consisted of flagging samples that had a total chlorophyll a concentration of zero, had fewer than four reported accessory pigments, or exceeded two standard deviations of the log-linear regression of total chlorophyll a with total accessory pigment concentrations. We anticipate the MAREDAT pigment database to be of use in the marine ecology, remote sensing and ecological modeling communities, where it will support model validation and advance our global perspective on marine biodiversity. The original dataset together with quality control flags as well as the gridded MAREDAT pigment data may be downloaded from PANGAEA: http://doi.pangaea.de/10.1594/PANGAEA.793246.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it