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Record W2261090192 · doi:10.26786/1920-7603(2014)2

Stimulation of flower nectar replenishment by removal: A survey of eleven animal-pollinated plant species

2014· article· en· W2261090192 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueJournal of Pollination Ecology · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNectarBiologyPhenologyBotanyPlant speciesEcologyPollen

Abstract

fetched live from OpenAlex

Understanding the interaction between reward-seeking flower feeding animals and plants requires consideration of the dynamic nature of nectar secretion. Studies on several plants suggest that nectar secretion may increase in response to its removal, but it is not clear whether the phenomenon is widespread. We determined whether 11 species of Colorado mountain wildflowers showed removal-enhanced nectar replenishment (RENR). We measured floral phenology, nectar volumes, rate of replenishment, and compared the cumulative nectar produced following five hourly removals with that accumulated after five hours. Nectar replenishment occurred rapidly, within minutes; statistically significant RENR was observed in 9 of our 11 study species, with the strongest effects in bee-pollinated species. We discuss the implications of RENR in plant species on the measurement of nectar, the adaptive advantage of RENR, and the energetic costs of RENR.

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.

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)0.001
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 score0.756
Threshold uncertainty score0.157

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.041
GPT teacher head0.232
Teacher spread0.191 · 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