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Record W2140391829 · doi:10.1071/zo12096

Foraging ecology of an Australian salt-pan desert ant (genus Melophorus)

2013· article· en· W2140391829 on OpenAlexaff
Patrick Schultheiss, Sebastian Schwarz, Ken Cheng, Rüdiger Wehner

Bibliographic record

VenueAustralian Journal of Zoology · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsMcMaster University
FundersAustralian Research Council
KeywordsForagingEcologyBiologyHabitatForageGenusNest (protein structural motif)

Abstract

fetched live from OpenAlex

Over the expanse of the salt lakes of the Lake Eyre basin lives a species of ant of the genus Melophorus (as yet unnamed), both on the edges of the salt-pan and on the salt-pan itself. Most of the foragers are small (~3.0–5.0 mm), but ~10% of the ants seen foraging are much larger (~7.0 mm) and may form a soldier caste. Foragers are thermophilic and show diurnal activity, displaying a single-peaked activity profile across the day, with activity time limited to 2–6 h at most each day (during the late-summer study period, 28 February to 28 March 2012). They forage largely for dead arthropods, but also occasionally bring home plant materials. Foraging success (not considering possible liquid food intake) is ~20%, resembling the success rate of their congener Melophorus bagoti, which inhabits cluttered environments. When displaced with food from a feeder, the ants head systematically and precisely in the feeder-to-nest direction, thus exhibiting path integration abilities involving celestial compass cues. The study of this species provides an interesting comparative perspective in contrasting desert ants of the same genus and thus genetic heritage inhabiting habitats differing in complexity of panoramic terrestrial cues as well as comparing ecologically similar species inhabiting the same type of habitat (in the present case, salt-pans) but differing in their phylogenetic relationships.

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 score0.278
Threshold uncertainty score0.752

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)0.0010.000

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 head0.273
Teacher spread0.256 · 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

Citations18
Published2013
Admission routes1
Has abstractyes

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