A SURROGATE APPROACH TO STUDYING THE CHEMICAL REACTIVITY OF BURROW MUCOUS LININGS IN MARINE SEDIMENTS
Bibliographic record
Abstract
Abstract Many infaunal marine invertebrates produce mucous excretions, composed primarily of the glycoprotein mucin, that play important roles in burrow stabilization. As with other biopolymers, the ionization of mucin provides highly reactive organic ligands that enable the sorption of metal cations from seawater. Owing to the difficulties in its isolation, however, the specific role of mucin in the adsorptive properties of animal secretions in marine environments is poorly understood. Here we apply a surface complexation approach to model proton and Cd adsorption behavior of partially purified Type III porcine gastric mucin (PGM), a commercially available analog to natural infaunal mucus. FTIR, proton and cadmium adsorption experiments indicate that Type III PGM mimics the acid-base and metal complexation behavior of natural mucous gels excreted by terebellid polychaete worms. At marine pH, nearly two-thirds of the total ligands in mucin-type glycoproteins are deprotonated and thus available to participate in metal cation adsorption reactions. Importantly, the concentration of available organic ligands in mucin exceeds (by up to 5 times) that of a variety of other metal-reactive organic compounds comprising the organic fraction of marine sediments. A substantial fraction of the dissolved organic matter in the bioturbated zone of marine sediments occurs in the form of mucin-associated glycoproteins; the availability of such organic materials may strongly influence the distribution of cations at the burrow margin.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".