Stalactite Growth Mediated by Biofilms: Example from Nani Cave, Cayman Brac, British West Indies
Bibliographic record
Abstract
Abstract Growth lines evident in cross sections through stalactites from Nani Cave provide a temporal record of their growth. Many of these dark, organic-rich laminae developed as biofilms that are recognized by the presence of (1) a diverse microbial biota that is dominated by actinomycetes, (2) calcified filaments, (3) films formed of extracellular polymeric substances (EPS), (4) grain-coating sheets of calcite crystals that grew in EPS, (5) biterminal calcite crystals, and (6) etching. This biosignatures suite encompasses a variety of constructive and destructive processes. Where fully developed, the features generated by the biofilms form a distinctive microstratigraphic succession, collectively < 50 μm thick, which can be traced laterally across the stalactite's surface. The use of speleothems in paleoclimate studies is commonly framed against a chronology that relies, at least in part, on annual growth couplets. The dark, organic-rich lamina that forms one part of the growth couplet is typically ascribed to abiotic precipitation that incorporated exogenic organic matter that was flushed into the cave following the first major rainfall of the wet season. This assumption ignores the possibility that dark, organic-rich growth laminae can be the record of biofilms that developed on the surface of the stalactites and hence, may not be a record of annual events.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| 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".