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Record W6948616277 · doi:10.5061/dryad.t4b8gtj19

Divergence in life history and behaviour between hybridizing Phymata

2021· dataset· en· W6948616277 on OpenAlexaff

Bibliographic record

VenueOpen MIND · 2021
Typedataset
Languageen
FieldComputer Science
TopicData Management and Algorithms
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsParapatric speciationDivergence (linguistics)Life history theoryLife historyGene flowNatural selectionJuvenileVertebrate

Abstract

fetched live from OpenAlex

Life history variation plays a central role in evolutionary and ecological processes, and may be especially pertinent to divergence in closely related species. We investigated life history differences in a pair of parapatric species of ambush bugs (Phymata) and a putative hybrid population. Despite the evidence of gene flow among these species, we found clear divergence between these parapatric populations for a suite of juvenile and adult life history traits including components of fitness. The higher latitude species was also less active, suggestive of potential divergence in dispersal. Increased melanism was correlated with longevity in one species, though it is unclear whether this relationship is causal. Observed life history differences between species were consistent with expectations of high-latitude species putting a premium on early or rapid development and increased reproductive rates. However, these results were not consistent with ‘pace-of-life syndromes’ at the species level. Individuals from the putative hybrid zone exhibited intermediate values for most traits though they had slower development, and reduced mobility, consistent with some previous work suggesting natural selection via hybrid breakdown.

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)0.001
metaresearch head score (Gemma)0.004
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.015
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.010

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 head0.082
GPT teacher head0.297
Teacher spread0.215 · 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
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
Published2021
Admission routes1
Has abstractyes

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