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Free-living ciliated protist diversity in the freshwater ecosystems of Delhi, India

2025· article· en· W4410973150 on OpenAlexaff
Jeeva Susan Abraham, Harpreet Kaur, S. Sripoorna, Santosh Kumar, Ilmas Naqvi, Swati Maurya, Daizy Bharti, Sandeep Antil, Jyoti Dagar, Komal Kamra, Ravi Toteja, Seema Makhija

Bibliographic record

VenueRecords of the Zoological Survey of India · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtist diversity and phylogeny
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsProtistDiversity (politics)EcologyBiologyEcosystemFreshwater ecosystemZoology

Abstract

fetched live from OpenAlex

A series of investigations was carried out on the freshwater free-living ciliate fauna from sixteen sites along the Yamuna River and various freshwater bodies in the Delhi region. These studies, conducted over the past 35 years, focused on the identification and documentation of ciliate diversity based on live-cell observations and silver staining techniques. In total, 104 species were documented, both from ongoing studies and published literature, representing 9 classes, 19 orders, 38 families, and 61 genera. Of these, one species, Sterkiella multicirrata (Li et al., 2018), is a new record for the Indian fauna. A large number of Spirotrich species were identified, along with a smaller proportion of ciliates belonging to classes Heterotrichea, Litostomatea, Phyllopharyngea, Oligohymenophorea, Prostomatea, and Colpodea. The highest ciliate diversity was observed in water samples from the Okhla Bird Sanctuary (OBS). Ciliate diversity and distribution recorded have been listed along with some photomicrographs.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.024
GPT teacher head0.243
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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