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Record W7044096476

Understanding Bumble Bee Community Changes And Floral Use In Southern Ontario.

2024· other· en· W7044096476 on OpenAlexafffundabout

Bibliographic record

VenueYork University Digital Library (York University) · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaYork UniversityGovernment of Ontario
KeywordsCompetition (biology)HabitatPollinatorHoney beeNicheApoideaHalictidae
DOInot available

Abstract

fetched live from OpenAlex

Multiple wild bee species, including bumble bees, are in global decline due to habitat loss, reduced floral resources, and competition with managed honey bees. Monitoring previously surveyed sites is essential to assess ongoing impacts on bumble bee populations and identify trends over time. This research revisited areas in southern Ontario to examine changes in bumble bee abundance, diversity, and floral use (Chapter 1) and explored potential competition for floral resources between bumble bees and honey bees (Chapter 2). Results indicate that while some bumble bee species have increased over the last 50 years, many have declined, leading to an overall loss of diversity. Findings also reveal significant niche overlap between bumble bees and honey bees, suggesting competition for floral resources. This work informs conservation strategies, identifies species requiring focused efforts, and emphasizes the importance of maintaining diverse floral resources to support bumble bee populations.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.082
GPT teacher head0.181
Teacher spread0.099 · 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
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
Published2024
Admission routes3
Has abstractyes

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