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Sources of variation in microscopic epibiont communities on intertidal rocky organisms in Niigata, Japan

2024· preprint· en· W4400681255 on OpenAlexafffund
Kanavillil Nandakumar, Yoshitake Takada

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsLakehead University
FundersLakehead UniversityNipissing University
KeywordsEpibiontIntertidal zoneVariation (astronomy)EcologyOceanographyGeographyGeologyBiologyPhysics

Abstract

fetched live from OpenAlex

Microscopic epibionts are important components of an intertidal ecosystem. However, because the epibionts are established on habitats provided by basibiont (host) organisms, the epibionts are affected by both the characteristics of basibionts and the environmental conditions on the shore. Here, we hypothesized that variations in the epibiont community were affected by the mobility, size, and surface roughness of the basibiont organisms, and environmental conditions during a one-month period in spring. Epibionts growing on 16 basibiont species belonging to Gastropoda, Bivalvia, Polyplacophora and Echinoidea, as well as those that had settled on plastic objects were collected from a rocky shore in Niigata, Japan. Most epibionts collected were diatoms, and the highest epibiont density was recorded on the surfaces of the limpet Cellana toreuma . The epibiont community changed significantly from April to May, and was also shaped by the characteristics of the basibionts. The results indicated that basibionts with sessile, large, or smooth surfaces had higher taxonomic richness, Simpson diversity, and epibiont density than those with mobile, small, or rough surfaces. Multivariate analysis of the epibiont community confirmed the importance of these basibiont characteristics and the survey month. Six groups of epibiont community were identified based on their contrasting sample communities, and each had their own indicator species. The results indicate that both environmental changes from April to May and changes in basibiont species promote changes in the epibiont community in this coastal region.

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 score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

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

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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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
Published2024
Admission routes2
Has abstractyes

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