Testate amoebae (Amorphea, Amoebozoa, Cercozoa) as bioindicators: a scientometric review
Bibliographic record
Abstract
Abstract: Aim The free-living protists testate amoebae are recognized as being bioindicators, able to reveal environmental alteration via remodifying richness, diversity and abundance of species. To assess the scientific production on the use of testate amoebae as bioindicators, a scientometric analysis was undertaken from 1960 to 2020. Methods The sourcing of scientific articles derived from Google Academic, Scielo, Science Direct and Online Library research platforms. All selected papers were factored according to chronology, journal of publication, country, authors’ affiliation, whether the study was empirical or experimentation, if it included solely testate amoebae or other groups of organisms, and aspects of the environment. Results A total of 215 papers from ninety-two journals revealed a notable increase in publication numbers over the last decades. The two journals that most published data on this theme were Microbial Ecology and Ecological Indicators. Whilst the largest number of papers was published in the European Continent, the countries that most contributed to the subject were Canada in the temperate region and Brazil in the tropics. Edward A.D. Mitchell published the largest number of studies and regarding institutions the Franche-Comté University. The majority of papers that associated testaceans as bioindicators were empirical, conducted with Thecamoebian inhabiting moss and as such, dissociated from other groups. Conclusions Despite a suggested uptick in research of testaceans as bioindicators, our results indicate a concentration of studies to limited regions of the globe. In another aspect, a great number of studies assess testaceans’ community as-a-whole, showing a shortage of in-depth knowledge into species and functional groups. Therefore, our survey points to a wide variety of aquatic ecosystems devoid of study matter, indicating the need to foster the research on testate amoeba's role as bioindicators especially in the tropical regions.
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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 | 0.033 | 0.114 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.191 | 0.184 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".