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Record W2919982225 · doi:10.3390/insects10030067

What Is the Carcass-Usage Mode of the Collembola? A Case Study of Entomobrya proxima in the Laboratory

2019· article· en· W2919982225 on OpenAlexaff
Lichao Feng, Liang Chang, Shaoqing Zhang, Xinyu Zhu, Sina M. Adl, Donghui Wu

Bibliographic record

VenueInsects · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversity of Saskatchewan
FundersProject 211
KeywordsBiologyCarrionTrophic levelInsectFood chainPredationPenicilliumAlternariaEcologyMicroorganismZoologyFood preferenceFood scienceBotanyBacteria

Abstract

fetched live from OpenAlex

Collembola display a variety of feeding habits, and prey on many types of food at different trophic levels in the soil. In most cases, their feeding selections are widely varied. In the interest of the food preferences of E. proxima, we attempted to confirm how the Collembola utilize food when feeding on carrion (unusual sources). Four different soil animals (with different stable isotope values and increasing trophic levels) were used to examine whether collembolans can use dead insects as a food resource in specific manners, depending on food preference. Our results demonstrated that the food preference of a collembolan changed significantly after feeding on insects with different feeding habits for 60 days. We found that stable isotope values (δ13C) of Entomobrya proxima approached those of the food sources. A large proportion of the diet (more than 50%) should directly consist of insect body parts, with the remainder consisting of indirectly used, mixed microorganisms naturally growing on animal food, such as fungi (Rhizopus sp., Alternaria sp., Penicillium sp., and Aspergillus sp.) and bacteria (Bacillus sp1. and Bacillus sp2.). Based on this research, the food preference of collembolans is more focused on carcasses (dead insect bodies) than microorganisms during the animal-food decomposition process.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.009
GPT teacher head0.253
Teacher spread0.245 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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