Assessment of sediment penetrability as an integrated in situ measure of intertidal softsediment conditions
Bibliographic record
Abstract
Infauna have an intimate relationship with the sediments they inhabit, and any study conducted upon infauna must, at the very least, describe sediment conditions. Common sediment assessments in intertidal systems include particle size distribution, as well as water and organic matter contents. These measures require extracting and processing a sediment core, and this disturbance may result in data that do not necessarily reflectin situconditions. Sediment penetrability measuredin situusing a penetrometer can circumvent this limitation. However, relationships between sediment penetrability and other sediment variables are poorly understood, especially in coastal systems. We evaluated the relationship between sediment penetrability and depth to the apparent redox potential discontinuity, mean particle size, organic matter content, and water content on tidal flats along the Pacific and Atlantic coasts of Canada. We also assessed whether adding penetrability into environmental models of the infaunal community improved model performance. We observed that while penetrability is statistically related to other sediment variables, relationships to covariates were weak. Further, inclusion of penetrability with other sediment variables improved the performance of models predicting infaunal community composition. Therefore, penetrability can be considered a separate variable, and contributes to an integrated assessment of environmental conditions experienced by biota. Finally, since we evaluated this method in different soft-sediment intertidal ecosystems (mudflats to sandflats), this method is applicable to a range of systems in other geographical areas.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 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".