Isotopic biosignatures in carbonate‐rich, cyanobacteria‐dominated microbial mats of the <scp>C</scp>ariboo <scp>P</scp>lateau, <scp>B.C.</scp>
Bibliographic record
Abstract
Photosynthetic activity in carbonate-rich benthic microbial mats located in saline, alkaline lakes on the Cariboo Plateau, B.C. resulted in pCO2 below equilibrium and δ(13) CDIC values up to +6.0‰ above predicted carbon dioxide (CO2 ) equilibrium values, representing a biosignature of photosynthesis. Mat-associated δ(13) Ccarb values ranged from ~4 to 8‰ within any individual lake, with observations of both enrichments (up to 3.8‰) and depletions (up to 11.6‰) relative to the concurrent dissolved inorganic carbon (DIC). Seasonal and annual variations in δ(13) C values reflected the balance between photosynthetic (13) C-enrichment and heterotrophic inputs of (13) C-depleted DIC. Mat microelectrode profiles identified oxic zones where δ(13) Ccarb was within 0.2‰ of surface DIC overlying anoxic zones associated with sulphate reduction where δ(13) Ccarb was depleted by up to 5‰ relative to surface DIC reflecting inputs of (13) C-depleted DIC. δ(13) C values of sulphate reducing bacteria biomarker phospholipid fatty acids (PLFA) were depleted relative to the bulk organic matter by ~4‰, consistent with heterotrophic synthesis, while the majority of PLFA had larger offsets consistent with autotrophy. Mean δ(13) Corg values ranged from -18.7 ± 0.1 to -25.3 ± 1.0‰ with mean Δ(13) Cinorg-org values ranging from 21.1 to 24.2‰, consistent with non-CO2 -limited photosynthesis, suggesting that Precambrian δ(13) Corg values of ~-26‰ do not necessitate higher atmospheric CO2 concentrations. Rather, it is likely that the high DIC and carbonate content of these systems provide a non-limiting carbon source allowing for expression of large photosynthetic offsets, in contrast to the smaller offsets observed in saline, organic-rich and hot spring microbial mats.
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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) | 0.000 | 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".