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Record W3164757141 · doi:10.3390/agronomy11061065

Self-Renewal of Invasive Goldenrods (Solidago spp.) as a Result of Different Mechanical Management of Fallow

2021· article· en· W3164757141 on OpenAlexaboutno aff
Dorota Gala-Czekaj, Agnieszka Synowiec, Teresa Dąbkowska

Bibliographic record

VenueAgronomy · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany and Plant Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSolidago canadensisInflorescenceBiomass (ecology)BiologyBiodiversityAgronomyWeed controlForbShootGrowing seasonPhenologyTILLINGInvasive speciesBotanyGrasslandEcology

Abstract

fetched live from OpenAlex

The spread of invasive plants is one of the most significant causes of biodiversity loss in natural, semi-natural, and anthropogenic habitats in Poland. This two-year study aimed to assess the rate of self-renewal of Canadian goldenrod (Solidago canadensis L.) and giant goldenrod (S. gigantea Aiton), and the possibility of achieving full generative development on fallow land restored to agricultural use with mechanical treatments. The following research objects were examined: the control (no mechanical treatments); one-time mowing; two-time mowing; one-time mowing plus one-time rotary tilling; and one-time mowing plus two-time rotary tilling. The phenological development of Solidago spp. was observed every 14 days from June to September each year. In October of each growing season, the aboveground parts of goldenrods’ biomass were measured, and selected morphological parameters were assessed. Two-time mowing and one-time mowing with two-time rotary tilling resulted in the highest reductions in the share of goldenrods in the generative stages of development, of 64.0% and 51.7% compared to the control, respectively. The two-time mowing treatment was the most effective at inhibiting goldenrods’ biomass accumulation, with a 57.7–77.0% decrease in biomass compared to the control. This treatment also reduced the number of flowering shoots and inflorescence lengths of both Solidago species.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.433

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 head0.015
GPT teacher head0.210
Teacher spread0.195 · 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 designBench or experimental
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

Citations15
Published2021
Admission routes1
Has abstractyes

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