Spectral features of biogenic calcium carbonates and implications for astrobiology
Bibliographic record
Abstract
Abstract The ability to discriminate biogenic from abiogenic calcium carbonate (CaCO3) would be useful in the search for extant or extinct life, since CaCO3can be produced by both biotic and abiotic processes on Earth. Bioprecipitated CaCO3material was produced during the growth of heterotrophic microbial isolates on medium enriched with calcium acetate or calcium citrate. These biologically produced CaCO3, along with natural and synthetic non-biologically produced CaCO3samples, were analysed by reflectance spectroscopy (0.35–2.5 μm), Raman spectroscopy (532 and 785 nm), and laser-induced fluorescence spectroscopy (365 and 405 nm excitation). Optimal instruments for the discrimination of biogenic from abiogenic CaCO3were determined to be reflectance spectroscopy, and laser-induced fluorescence spectroscopy. Multiple absorption features in the visible light region occurred in reflectance spectra for most biogenic CaCO3samples, which are likely due to organic pigments. Multiple fluorescence peaks occurred in emission spectra (405 nm excitation) of biogenic CaCO3samples, which also are best attributed to the presence of organic compounds; however, further analyses must be performed in order to better determine the cause of these features to establish criteria for confirming the origin of a given CaCO3sample. Raman spectroscopy was not useful for discrimination since any potential Raman peaks in spectra of biogenic carbonates collected by both the 532 and 785 nm lasers were overwhelmed by fluorescence. However, this also suggests that biogenic carbonates may be identified by the presence of this organic-associated fluorescence. No reliable spectroscopic differences in terms of parameters such as positions or widths of carbonate-associated absorption bands were found between the biogenic and abiogenic carbonate samples. These results indicate that the presence or absence of organic matter intimately associated with carbonate minerals is the only potentially useful spectral discriminator for the techniques that were examined, and that multiple spectroscopic techniques are capable of detecting the presence of associated organic materials. However, the presence or absence of intimately associated organic matter is not, in itself, an indicator of biogenicity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".