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Record W3013261122 · doi:10.1139/cjb-2019-0209

Hiding in plain sight: experimental evidence for birds as selective agents for host mimicry in mistletoes

2020· article· en· W3013261122 on OpenAlexvenueno aff
Martha E. Cook, Andrea Leigh, David M. Watson

Bibliographic record

VenueBotany · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsnot available
FundersNational Parks and Wildlife ServiceAustralian GovernmentBirdLife Australia
KeywordsBiologyLoranthaceaeMimicryHost (biology)Parasitic plantGuildEcologyHost specificityZoologyBotanyHabitat

Abstract

fetched live from OpenAlex

Many Australian mistletoe species are cryptic, closely resembling their host foliage and overall appearance. Seed-dispersing birds have been proposed as a selective agent for host resemblance, with cryptic mistletoes only located by thoroughly searching through canopies regardless of infection status, boosting mistletoe populations by increasing the frequency of seeds dispersed to uninfected hosts; however, this idea is as yet untested. We measured bird visitation to fruiting mistletoes (n = 20) over two consecutive days, with manual defoliation of the mistletoe occurring before observation began on the second day to determine the effect of the visual appearance of the mistletoe on potential seed-dispersing birds, expecting defoliation to reduce the number of visits. Visits to the mistletoes were compared between days of observation and dietary guild (mistletoe specialist/nonspecialist). Intact mistletoes were visited more than the defoliated mistletoes, and the dietary guilds differed in their visitation patterns. This work demonstrates that the visual acuity of seed-dispersers can distinguish subtle differences in mistletoe phenotypes within infected hosts, consistent with the hypothesis that those mistletoes that more closely resemble their hosts are more difficult to perceive from afar and therefore more likely to have their seeds dispersed to uninfected hosts.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score0.189

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 head0.075
GPT teacher head0.303
Teacher spread0.229 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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