Expansion of the Conceptual Model for the Accumulation of Selenium in Lentic Food Chains to Include Redox-Controlled Generation and Diffusion of Selenite and Dissolved Organo-Selenium Compounds
Bibliographic record
Abstract
The controls governing the availability of reduced selenium (Se) species, namely selenite (Se[IV]) and dissolved organo-Se (DOSe), to primary producers at the sediment-water interface in depositional environments (i.e., lentic systems) were assessed through consideration of theoretical principles and field data. Selenite is generated in suboxic sediment porewater via the microbially mediated reduction of selenate (Se[IV]) and/or reductive dissolution of Se-bearing iron oxides. Field data for lentic environments demonstrate that the production of DOSe in sediment porewaters can also be redox- and depth-dependent. In this manner, the remobilization depths of Se(IV) and DOSe in depositional environments are dependent on the vertical redox gradient (dEh/dz), where deeper depths of remobilization are observed in less reducing sedimentary environments (lower dEh/dz). In turn, remobilization depth has a direct bearing on the concentration of dissolved Se(IV) and DOSe that may be realized at the sediment-water interface because the depth of reaction governs the diffusive path length, concentration gradient, and rate of diffusional transport toward the sediment-water interface. The principles that link sediment redox gradients, depth of remobilization, diffusive transport processes, and concentration of reduced Se species at the sediment-water interface have a direct bearing on the potential for Se uptake by primary producers in lentic food chains (e.g., phytoplankton, biofilms, bacteria). Overall, these processes complement the current conceptual "benthic detrital food chain" model that describes the accumulation of Se in lentic systems. Environ Toxicol Chem 2022;41:2859-2869. © 2022 SETAC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".