The Australian Chlorophyll a Database (1965 - 2017)
Bibliographic record
Abstract
Chlorophyll a is the most commonly used indicator of phytoplankton biomass and is a proxy for primary productivity in the marine environment. It is relatively simple and cost effective to measure when compared to phytoplankton abundance and is thus routinely included in many surveys. Here we collate 173,333 records of chlorophyll a collected since 1965 from Australian waters gathered from researchers on regular coastal monitoring surveys to long ocean voyages. This dataset concentrates on samples analysed using spectrophotometry, fluorometry and high performance liquid chromatography (HPLC). Here we collate all available chlorophyll a data from Australian waters, gathered from researchers, students, government bodies, state agencies, councils and databases, along with the associated metadata. The Australian Chlorophyll a Database is available through the Australian Ocean Data Network portal (AODN: https://portal.aodn.org.au/ ), the main repository for marine data in Australia. The Australian Chlorophyll a Database will be maintained and updated through the CSIRO data centre, with periodic updates sent to the AODN. A snapshot of the Australian Chlorophyll a Database at the time of this publication has been assigned a DOI and will be maintained in perpetuity by the AODN. These data can be used in isolation as an index of phytoplankton biomass or in combination with other data to provide insight into water quality, ecosystem state, and / or the relationships with other trophic levels such as zooplankton or fish. This metadata record was based on the following CSIRO metadata record: https://www.marlin.csiro.au/geonetwork/srv/en/search?uuid=4c72fe3b-bddf-44da-a809-1791033a6ac5.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.015 |
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".