NEOICHNOLOGICAL EXPRESSIONS OF SALINITY VARIABILITY: TESTING ICHNOLOGICAL PROXIES IN THE GIRONDE ESTUARY AND ARCACHON BAY, FRANCE
Bibliographic record
Abstract
Abstract This study evaluates neoichnological characteristics of the Gironde Estuary and Arcachon Bay to test ichnological proxies of salinity conditions along a freshwater to marine gradient. Both the Gironde Estuary and Arcachon Bay are classified as mixed-influence (wave-tide) estuaries, but tidal currents are stronger and turbidity is higher in the Gironde Estuary funnel than in Arcachon Bay. Trace distributions and the size-diversity index (SDI) are determined at various localities in both systems and are then compared to trends established in prior studies. Results indicate that SDI provides a robust, quantitative correlation with salinity that is comparable to geochemical and biological proxies. Trace (ichno) diversity alone reflects salinity qualitatively but is limited by sampling and human (interpretation) biases and data variability. These findings contribute to better understanding the predictive value and limitations of SDI in modern estuaries. However, the application of SDI in the sedimentary record requires additional research as neither infaunal diversity nor vermiform burrows can be established reliably therein.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".