An exploration of microbial response to stressors with Prof. Claudio C. Vásquez Guzmán
Bibliographic record
Abstract
Microorganisms, particularly bacteria, are the major species on the planet, considered to be up to 98% of all species.Bacteria have evolved impressive responses to various stressors, which have been essential for the adaptation and evolution of microorganisms and colonization of a wide range of environments.This special issue of Biological Research on microbial response to stressors is a tribute of the Chilean and international scientific community to the late Professor Claudio C. Vásquez Guzmán (1952-2020) who dedicated his career in environmental microbiology and biochemistry to the study of bacterial stress response, particularly that of metal ion stress.Microbes were the first living cells on Earth.They have co-evolved with the planet and thus have experienced a wide range of geological changes that have produced a wide variety of ecological niches and stressors.Stressors to microbial life include expected physical and chemical concerns such as: temperature, pressure, redox state, pH, ionic strength, osmolarity, UV light exposure and shear forces.Additionally, other stressors exist such as low availability of key nutrients, carbon sources, scarcity in electron acceptors, antimicrobial compounds, and also anthropogenicproduced or released pollutants that include toxic metals.A wide range of natural extreme environments that are inhabited by extreme microorganisms are present world-wide.However, Chile has remarkable diversity, from the Atacama Desert and Altiplano highlands in the North to Patagonia and Antarctic regions in the South, and from South Pacific and Rapa Nui Island in the West to the Andes Mountains in the East [1].In addition, polluted environments due to anthropogenic activities (e.g., mining, petroleum transport and processing, chemical
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.010 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".