Seaweed aquaculture: the case of Laminaria digitata
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the last 20 years, algae cultivation and production has increased significantly and plays an important role in the fishing industry.Global algae production in 2022 was estimated at more than 35 million tonnes.Algae, in their various forms, have a multitude of applications that enhance the social and economic importance of cultivation worldwide.The European market for algae is expanding due to the growing demand for alternative and sustainable sources of protein and products with nutritional benefits.Consequently, the cultivation of various types of micro-and macro-algae is also increasing.The present study compiles information from the international literature on the cultivation of macroalgae, particularly of Laminaria digitata, an endemic species of northern Europe and the west coast of North America and Canada.A description is given of its cultivation in a longline system, which includes the growth of the algae in both laboratory , and natural aquatic environments.A number of socio-economic and environmental benefits, as well as various uses of the species, are then discussed.These include: its use as food for humans and VI animals; its contribution to the pharmaceutical industry through the various extracts it produces (e.g.alginates, carrageenans, chlorotannins); and the potential substitution of fossil raw materials through the production of bioplastics and biofuels.Positive environmental impacts are highlighted, such as the provision of ecosystem services (e.g.for the assessment of water quality characteristics and the restoration of polluted marine systems through the capture of nitrogen, phosphorus and other substances).Finally, the challenges of macroalgae cultivation are highlighted and the need to provide incentives at all stages of the product value chain, from the research stage, to the primary sector and the market, in order to create a solid basis for the sustainable development of the sector.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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