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Record W7014774243

The relative importance of olfactory signaling to fly-moss
\nspore dispersal network structure of two sympatric moss
\nspecies in Newfoundland, Canada

2019· dissertation· en· W7014774243 on OpenAlexaboutno aff

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2019
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicBryophyte Studies and Records
Canadian institutionsnot available
Fundersnot available
KeywordsCarnivoreSympatric speciationBiological dispersalMossOlfactory cuesMarsupial
DOInot available

Abstract

fetched live from OpenAlex

In Newfoundland, Splachnum ampullaceum (herbivore dung scent mimic) and S. \npensylvanicum (omnivore dung scent mimic) grow in bogs on summer moose (Alces \nalces L.) dung and via olfactory and visual deception have their spores dispersed to \ndung by flies. In Chapter 2, the addition of carnivore and herbivore-mimicking scent \nincreased the number of visiting flies, and the addition of carnivore scent attracted \ncarrion flies, and this effect was greatest for S. pensylvanicum. In Chapter three \nconsecutive years of fly trapping data for both species of moss were compared using \nNetwork analyses. Results showed that both mosses attract a generalized fly fauna \n(lower network specialization (H₂average) 0.171), most of which are also associated \nwith summer moose dung (average connectance low 0.799). Also, the fly faunas of S. \nampullaceum and S. pensylvanicum did not differ from each other in all three years.

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)0.000
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 score0.089
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.226
Teacher spread0.210 · 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
Published2019
Admission routes1
Has abstractyes

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