Collection of the proteus-type amoebae at the Institute of Cytology, Russian Academy of Sciences. I. History, goals and research fields
Bibliographic record
Abstract
Summary Amoebae Culture Collection at the Institute of Cytology RAS in St. Petersburg (Russia) – ACCIC (SPb) – was founded in 1960; it includes strains (clones) of large free living freshwater amoebae of Amoeba proteus -type (family Amoebidae). These protists have been extensively used as model organisms in cell biology for almost two centuries. The amoebae strains were originally received from a number of laboratories and collections of cell cultures in many countries; some strains were raised from the samples isolated directly from nature in various regions of the world. Many of the strains in the ACCIC have been thoroughly characterized. In this paper, history of the Collection and its application in different scientific research fields are briefly presented. Key words: Amoebae, Amoeba , free living freshwater amoebae, strains collection It is well known that the collections of living organisms play a key role in various modern experi-mental biological investigations. In addition to huge national collections – for example, such as the American Type Culture Collection (ATCC), there exist also many specialized zoological, botanical, and microbiological collections that are maintained in some scientific institutions or laboratories; the examples are: Culture Collection of Algae and Protozoa (CCAP), National Center for Marine Algae and Microbiota (NCMA), Canadian Center for the Culture of Microorganisms (CCCM), All-Russian Collection of Microorganisms (VKM), and many others. They are extremely important when different taxonomic groups of organisms are studied. Amoebae of the
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.008 |
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".