Tracking Pre- and Post-Industrialization Changes in the Bay of Sept-Îles, Canada, Using Foraminifera as Bioindicators
Bibliographic record
Abstract
Joshi, N.; Montero-Serrano, J.-C.; Lefebvre, C., and Saulnier-Talbot, É., 2025. Tracking pre- and post-industrialization changes in the Bay of Sept-Îles, Canada, using foraminifera as bioindicators. Journal of Coastal Research, 41(2), 255–271. Charlotte (North Carolina), ISSN 0749-0208. A multiproxy analysis of a short sediment core retrieved from the Bay of Sept-Îles (Quebec, Canada) allowed for better understanding of changes in geochemical composition and foraminiferal assemblages during the pre- and post-industrial periods (i.e. before and after 1900 Common Era [CE]). The vertical distribution of the major elements suggests that environmentally consequential colonial activities in Sept-Îles began around the 1860s CE. Elemental analysis showed fluctuations in metal concentrations, with marked shifts in iron, manganese, and calcium levels between the pre- and post-industrial periods. Furthermore, a synchronous shift from calcareous to agglutinated foraminifera suggests a stressful environment for the calcareous species, potentially influenced by factors such as calcium limitation and carbonate dissolution. Species belonging to the genera Reophax and Miliammina and Spiroplectammina biformis showed tolerance of the changing environmental conditions within the bay. Overall, the findings emphasize that none of the element concentrations is above contamination threshold but rather that the shift in the source provenance and escalation in the relative prevalence of metals, especially iron, demands careful consideration because it potentially signifies alterations of environmental conditions. Moreover, the results highlight the sensitivity of foraminifera to environmental changes and their utility as bioindicators of stress in coastal marine ecosystems, providing valuable insights into past and present conditions of the Bay of Sept-Îles and other similar environments.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".