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Record W2969502424 · doi:10.1017/inp.2019.21

Phenology of seed maturation in babysbreath (Gypsophila paniculata) in northwest Michigan, USA, and its relation to glyphosate efficacy

2019· article· en· W2969502424 on OpenAlexaboutno aff
Emma Rice, Pamela Martínez-Oquendo, James N. McNair

Bibliographic record

VenueInvasive Plant Science and Management · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
FundersNature ConservancyNational Park ServiceRoyal Botanical Gardens, KewU.S. Environmental Protection AgencyNational Science Foundation
KeywordsPhenologyGerminationBiologyPerennial plantGrowing seasonPopulationAgronomyGlyphosateSeedlingHorticultureDemography

Abstract

fetched live from OpenAlex

Abstract Babysbreath or perennial babysbreath ( Gypsophila paniculata L.) is an aggressive invasive plant in large parts of southern Canada and the northern and western United States. It reproduces and disperses by seed, so the phenology of seed maturation is important in designing management programs. The present study provides the first quantitative assessment of G. paniculata seed-maturation phenology in a field population, as well as the first quantitative assessment of how the efficacy of herbicide treatment in preventing production of germinable seeds depends on the timing of treatment in relation to this phenology. Seeds were collected from untreated plants on five dates during July and August in both 2016 and 2017 and tested for germinability. Percent germination increased from 20% to 81% between July 22 and 28 and exceeded 90% by August 4, 2016. The seed-maturation phenology in 2017 was similar but delayed by about 4 d. On a growing degree-day scale, seed-maturation phenologies for the 2 yr were nearly identical. We also tested germinability of seeds from plants sprayed with glyphosate (23.4 ml ae L −1 ) on July 11, 18, and 25, 2016 (one date per plant). Percent germination increased from 0% to 13% to 20% over successive treatment dates, highlighting the importance of completing treatment early in the growing 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 score0.671
Threshold uncertainty score0.991

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 head0.025
GPT teacher head0.206
Teacher spread0.181 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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