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Record W4410004957 · doi:10.1080/11956860.2025.2494407

The abundance and reproductive success of the orchid <i>Calypso bulbosa</i> L. in relation to forest structure

2025· article· en· W4410004957 on OpenAlexvenueno aff
Esa Huhta

Bibliographic record

VenueEcoscience · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
FundersForest Research Institute
KeywordsAbundance (ecology)BiologyReproductive successRelation (database)EcologyBotanyOrchidaceaePopulationDemographySociology

Abstract

fetched live from OpenAlex

This seven-year study investigated the effects of forest structure and fragmentation on the Calypso orchid (Calypso bulbosa) (Orchidaceae). The species was found to prefer growing sites in the interior of the forest and near small openings. Proximity to clear-cuts and to openings had no effect on reproductive success. High canopy cover and shrub cover reduced the number of plants, while high shrub cover reduced the number of flowering plants. This in turn may affect the behaviour of bumblebees (Bombus spp.), the main pollinators of the Calypso orchid, and their ability to find and pollinate a plant. The number of flowering and pollinated plants was higher in large populations than in small ones. The long-term reproductive success of large populations, as measured by flower and fruit production, was more stable than that of small populations. Despite its status as a strictly protected species, the Calypso orchid is threatened by forest management, particularly in privately owned forests. Nature-friendly harvesting methods, such as selection harvesting and small-gap harvesting without soil preparation, may prove to be appropriate forest management practices in the species’ sites.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.205
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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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