Identifying microbial life in rocks: Insights from population morphometry
Bibliographic record
Abstract
The identification of cellular life in the rock record is problematic, since microbial life forms, and particularly bacteria, lack sufficient morphologic complexity to be effectively distinguished from certain abiogenic features in rocks. Examples include organic pore-fillings, hydrocarbon-containing fluid inclusions, organic coatings on exfoliated crystals and biomimetic mineral aggregates (biomorphs). This has led to the interpretation and re-interpretation of individual microstructures in the rock record. The morphologic description of entire populations of microstructures, however, may provide support for distinguishing between preserved micro-organisms and abiogenic objects. Here, we present a statistical approach based on quantitative morphological description of populations of microstructures. Images of modern microbial populations were compared to images of two relevant types of abiogenic microstructures: interstitial spaces and silica-carbonate biomorphs. For the populations of these three systems, the size, circularity, and solidity of individual particles were calculated. Subsequently, the mean/SD, skewness, and kurtosis of the statistical distributions of these parameters were established. This allowed the qualitative and quantitative comparison of distributions in these three systems. In addition, the fractal dimension and lacunarity of the populations were determined. In total, 11 parameters, independent of absolute size or shape, were used to characterize each population of microstructures. Using discriminant analysis with parameter subsets, it was found that size and shape distributions are typically sufficient to discriminate populations of biologic and abiogenic microstructures. Analysis of ancient, yet unambiguously biologic, samples (1.0 Ga Angmaat Formation, Baffin Island, Canada) suggests that taphonomic effects can alter morphometric characteristics and complicate image analysis; therefore, a wider range of microfossil assemblages should be studied in the future before automated analyses can be developed. In general, however, it is clear from our results that there is great potential for morphometric descriptions of populations in the context of life recognition in rocks, either on Earth or on extraterrestrial bodies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".