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Record W2528625961 · doi:10.1002/ecy.1528

Global associations between birds and vane‐dwelling feather mites

2016· article· en· W2528625961 on OpenAlexaff
Jorge Doña, H. C. Proctor, Sergey V. Mironov, David Serrano, Roger Jovani

Bibliographic record

VenueEcology · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBird parasitology and diseases
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFeatherEcologyBiologyHost (biology)MacroecologyFlight featherMiteZoologyBiogeography

Abstract

fetched live from OpenAlex

Understanding host-symbiont networks is a major question in evolutionary ecology. Birds host a great diversity of endo- and ectosymbiotic organisms, with feather mites (Arachnida: Acariformes: Analgoidea, Pterolichoidea) being among the most diverse of avian symbionts. A global approach to the ecology and evolution of bird-feather-mite associations has been hampered because of the absence of a centralized data repository. Here we present the most extensive data set of associations between feather mites and birds. Data include 12 036 records of 1887 feather mite species located on the flight feathers of 2234 bird species from 147 countries. Feather mites typically located inside quills, on the skin, or on downy body feathers are not included. Data were extracted from 493 published sources dating from 1882 to 2015. Data exploration shows that although most continents and bird families are represented, most bird species remain unexplored for feather mites. Nevertheless, this is the most comprehensive data set available for enabling global macroecological analyses of feather mites and their hosts, such as ecological network analyses. This metadata file outlines the structure of these data and provides primary references for all records used.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

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)0.0010.001

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 head0.013
GPT teacher head0.267
Teacher spread0.254 · 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; both teacher heads agree on what is shown here.

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

Citations38
Published2016
Admission routes1
Has abstractyes

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