MétaCan
Menu
Back to cohort
Record W3016966229 · doi:10.1111/jeb.13633

Delusions of grandeur: Seed count is not a good fitness proxy under individual variation in phenology

2020· article· en· W3016966229 on OpenAlexafffund
Lina Wen, Andrew M. Simons

Bibliographic record

VenueJournal of Evolutionary Biology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyPhenologyVariation (astronomy)Proxy (statistics)EcologyZoologyStatisticsMathematics

Abstract

fetched live from OpenAlex

The concept of fitness is central to evolutionary biology, yet it is difficult to define and to measure. In plant biology, fitness is often measured as seed count. However, under an array of circumstances, seed count may be a biased proxy of fitness, for example when individuals vary in allocation to sexual versus asexual reproduction. A more subtle example, but also likely to be important in natural populations, is when interindividual variation in conditions during development results in variation in offspring quality among seed parents. In monocarpic (semelparous) plants, this is expected to result from variation in effective season length experienced among individuals that reach reproductive maturity at different times. Here, we manipulate growing season length to ask whether seed count is an accurate representation of parental fitness in the monocarpic herb Lobelia inflata. Simple seed count suggests a paradoxical fitness advantage under constrained-season length. However, we find that the apparent fitness advantage of a constrained-season length is overridden by low relative per-seed fitness. Furthermore, the fitness deficit in the constrained environment is associated primarily with an accelerating decrease in viability and seedling survival in seeds derived from fruits produced progressively later in the season. In this study, the overall fitness value of a seed under a constrained season is 0.774 of that observed under a long season.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.526
Threshold uncertainty score0.146

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.060
GPT teacher head0.238
Teacher spread0.178 · 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.

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

Citations4
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Evolutionary BiologySame topicPlant and animal studiesFrench-language works237,207