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Record W2253087249 · doi:10.3389/fmicb.2016.00016

Aerobiology Over Antarctica – A New Initiative for Atmospheric Ecology

2016· article· en· W2253087249 on OpenAlexaff
David A. Pearce, Irina A. Alekhina, Aleks Terauds, Annick Wilmotte, Antonio Quesada, Arwyn Edwards, Aurélien Dommergue, Birgit Sattler, Byron J. Adams, Catarina Magalhães, Wan-Loy Chu, Maggie C. Y. Lau, S. Craig Cary, David J. Smith, Diana H. Wall, Gabriela Eguren, Gwynneth F. Matcher, James A. Bradley, Jean‐Pierre de Vera, Josef Elster, Kevin A. Hughes, Lewis Cuthbertson, Liane G. Benning, Nina Gunde‐Cimerman, Peter Convey, Soon Gyu Hong, Steve B. Pointing, Vivian H. Pellizari, Warwick F. Vincent

Bibliographic record

VenueFrontiers in Microbiology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsUniversité Laval
FundersInstitut Polaire Français Paul Emile VictorAgence Nationale de la RechercheScientific Committee on Antarctic ResearchNatural Environment Research CouncilSight Research UK
KeywordsAerobiologyEcologyMicrobial ecologyEnvironmental scienceGeographyBiology

Abstract

fetched live from OpenAlex

The role of aerial dispersal in shaping patterns of biodiversity remains poorly understood, mainly due to a lack of coordinated efforts in gathering data at appropriate temporal and spatial scales. It has been long known that the rate of dispersal to an ecosystem can significantly influence ecosystem dynamics, and that aerial transport has been identified as an important source of biological input to remote locations. With the considerable effort devoted in recent decades to understanding atmospheric circulation in the south-polar region, a unique opportunity has emerged to investigate the atmospheric ecology of Antarctica, from regional to continental scales. This concept note identifies key questions in Antarctic microbial biogeography and the need for standardized sampling and analysis protocols to address such questions. A consortium of polar aerobiologists is established to bring together researchers with a common interest in the airborne dispersion of microbes and other propagules in the Antarctic, with opportunities for comparative studies in the Arctic.

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)0.003
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.009
GPT teacher head0.234
Teacher spread0.225 · 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 designNot applicable
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

Citations80
Published2016
Admission routes1
Has abstractyes

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