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Record W6967182650 · doi:10.5061/dryad.tdz08kq7h

Minimal assay detects population-level senescence in the aquatic plant Lemna minor

2024· dataset· en· W6967182650 on OpenAlexaff

Bibliographic record

VenueDRYAD · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsSenescenceLemna minorPetri dishPopulationAquatic plantLemna

Abstract

fetched live from OpenAlex

At the population level, senescence occurs when older individuals have an increased risk of death and reduced reproduction compared to younger individuals. We investigated senescence in the aquatic plant Lemna minor (common duckweed), an important species for plant senescence research. Our objectives were to (1) confirm or refute the presence of population-level senescence in this model species; (2) develop a minimal assay of senescence requiring only once-weekly data collection; and (3) test whether there were appreciable differences in senescence in plants grown in glass compared to polystyrene petri dishes, with an aim to reducing single-use plastic waste and long-term research materials costs. We found that weekly survival arced downward with age when viewed on a semi-log plot, and weekly production of descendants decreased with age, with both findings indicating population-level senescence that matched previous work using more frequent data-collection (per Objectives 1 and 2). Additionally, we found no noteworthy differences in senescence between plants grown in glass versus polystyrene petri dishes (per Objective 3). The use of weekly data collection could liberate personnel resources for other research-group functions, and could make the Lemna system suitable for senescence- or demography-education exercises. The use of glass dishes could reduce lab waste and expense.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.059
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.060

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 head0.045
GPT teacher head0.293
Teacher spread0.248 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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 routes1
Has abstractyes

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