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Record W7038364433

The ice-nucleating activity of fertile soils and crop pathogens

2024· dissertation· en· W7038364433 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWhite Rose eTheses Online (University of Leeds, The University of Sheffield, University of York) · 2024
Typedissertation
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsnot available
Fundersnot available
KeywordsSoil waterAgricultureAerosolCropIce nucleusParticle (ecology)Supercooling
DOInot available

Abstract

fetched live from OpenAlex

Atmospheric ice formation plays a key role in controlling the radiative properties and lifetimes of supercooled clouds. Ice-nucleating particles, which initiate the heterogeneous nucleation of ice in supercooled clouds, are rare in the atmosphere and crucial for the formation of ice in clouds. Therefore, our understanding of the sources and atmospheric concentrations of ice-nucleating particles is critical for our understanding of the impact of clouds on the climate. Biological aerosol particles have been identified as potentially important ice nucleators, particularly at temperatures above -10°C. However, our current understanding of the relative contribution of biological material to regional and global ice-nucleating particle populations remains poor. In particular, crop agriculture contributes up to 25% of global dust emissions, creating a potentially important source of biological ice-nucleating particles which is yet to be fully understood. This thesis investigated different agricultural sources of ice-nucleating particles with the overall goal of determining the extent to which agriculture influences regional and global ice-nucleating particle populations. Agricultural soil samples from the UK and Canada were extracted to examine the ice-nucleating activity of the submicron entities within the soil. This analysis revealed that the ice-nucleating activity of agricultural soils from different locations varied significantly but this variation was not attributable to concentrations of surfactants within the soil. The ice-nucleating activity of two common fungal crop pathogens was also analysed to determine the relative influence of crop agriculture on the regional ice-nucleating particle populations, which indicated that the ice-nucleating activity of these spores was stable when stored. Finally, the size-resolved ice-nucleating particle concentrations of agricultural soil samples were analysed using a lab-based aerosol chamber technique which showed that the ice-nucleating activity of agricultural soils is evenly distributed across its size distribution. Through these techniques, we have been able to unpick some of the complexities in understanding agricultural sources of ice-nucleating particles by highlighting the potential importance of biological, macromolecular substances to the ice-nucleating activity of these soils.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.014
GPT teacher head0.216
Teacher spread0.202 · 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