Concrete design and biotic colonization at the interface with the human user
Bibliographic record
Abstract
Concrete coastal structures, at the interface of land and sea, are increasing in response to population pressure and rising sea levels. Maximizing biodiversity on these artificial structures is being approached using various eco-engineering methods, as an opportunity for bioreceptivity, but less attention has been given to how their biotic colonization will affect human users. Biotic composition and succession have an impact on the human use of the structures, as algae have varying levels of slipperiness, hence danger for users, and also influence degradation of concrete. The ecological engineering study reported in this article determined variation in biotic colonization among different concrete designs. Experimental blocks were deployed for 1 year in the intertidal zone to test differences in colonization among (i) a range of concrete mixes: manufactured with ordinary Portland cement (OPC); rapid hardening Portland cement (RHPC); OPC with microsilica (MS); and OPC with ground granulated blast furnace slag (GGBS) and (ii) different surface texture: surface obtained with controlled permeability formwork (CPF); trowel finished surface; surface obtained with wooden formwork; and patterned finish. Differences in algal colonization among different concrete mixes persisted for 9 of 12 months, with microsilica concrete having consistently higher algal coverage than other types of concretes. Surface finishes had a greater effect: in particular on CPF blocks, low algal growth and high grazer activity left the surface clear after 1 year of deployment, whereas trowel, formwork and patterned finishes had increasingly rapid colonization. Understanding the significance of concrete engineering techniques for ecological processes of an increasingly man-made coastline interfaces engineering with biology and applies to coastal ecosystems worldwide. Our study has shown through the integration of ecology and concrete engineering technology that techniques such as using CPF can greatly influence the resulting assemblages and hence affect attributes such as slipperiness (for users) and the speed of concrete erosion.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".