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Record W3044018977 · doi:10.12789/geocanj.2020.47.155

Geoscience in the Time of Covid

2020· article· en· W3044018977 on OpenAlexvenueaboutno aff
Andrew Kerr

Bibliographic record

VenueGeoscience Canada · 2020
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakComputer scienceBiologyVirologyMedicineInfectious disease (medical specialty)Internal medicine

Abstract

fetched live from OpenAlex

If one thing is beyond discussion in June of 2020, it is that we are living in unique times, even if pandemics are far from unique in longer Human history.A short article in this issue on the topical concept of the Anthropocene closes with a quote that (in part) reads that "....some humility is in order about our, thus far, infinitesimal part in the history of the planet".Our high-technology society has certainly received a stark reminder of the power of the natural world, as it struggles to prevail over one of the most primitive of life forms.Few previous analyses of the pandemic threat that I have read fully captured the economic impacts and ethical dilemmas that confront us in this time of Covid.Many in the Canadian Geoscience Community suffered these impacts and some are now directly touched by illness or bereavement.On behalf of those involved in Geoscience Canada, I extend sympathies and condolences, and the hope that the time of Covid will be brief.The American Geological Institute (AGI) recently initiated a study on the impacts of Covid-19 on the Geosciences and invited contributions from member organizations (see www.americangeosciences.org/workforce/covid19).No great insight is needed to see how the prohibition of large gatherings and the need for physical distancing could have far-reaching implications for many of the things that we typically do.We will need to think about how to conduct important field work, especially in remote and isolated areas, how to mount our vital professional conferences, and how to educate the next generation of Geoscientists.We should expect that the global pandemic will wreak changes to many other things that we have not yet considered.AGI's initiative is a good step, and one that will hopefully provide some direction and context as we move into next year.There are of course much wider questions to consider, such as whether this global crisis might force society to better confront the threat of climate change or even to rethink the relationship between the Human and Natural worlds.

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)0.014
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.909
Threshold uncertainty score0.477

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0200.014
Scholarly communication0.0150.006
Open science0.0020.007
Research integrity0.0070.012
Insufficient payload (model declined to judge)0.0300.004

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 head0.191
Teacher spread0.178 · 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
GenreCommentary

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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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