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Record W38369588 · doi:10.1002/mdc3.13999

Remote Deep Brain Stimulation Programming in Canada.

2024· preprint· en· W38369588 on OpenAlexaffabout
Mauro Vigani, Dillen Koen, Rodriguez Cerezo Emilio

Bibliographic record

VenuePubMed · 2024
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsKrembil FoundationUniversity of TorontoToronto Western Hospital
Fundersnot available
KeywordsFood securityProductivityAgricultureAgricultural economicsWorld populationEuropean unionBusinessAgricultural productivityPopulationProduction (economics)Consumption (sociology)Action planStaple foodPosition (finance)Natural resource economicsInternational tradeAgricultural scienceGeographyEconomicsEconomic growthDeveloping countryEnvironmental science

Abstract

fetched live from OpenAlex

The Institute for Prospective Technological Studies (IPTS) of the European Commission’s Joint Research Centre (JRC) is starting a new research line with the aim to describe the current situation and analyze the elements affecting wheat yields and wheat farming productivity. To scope the issue, the JRC organised a workshop on "Wheat productivity in the EU: determinants and challenges for food security and for climate change" in Seville on 22nd and 23rd November 2012. \nThis JRC Scientific and Policy Report provides the proceedings of the workshop, that covered the following topics:\n\nSession 1: Wheat productivity trends in Europe and world-wide\nSession 2: Innovation in production factors affecting wheat productivity\nSession 3: Policies and regulations affecting wheat productivity\nSession 4: Outlook on wheat productivity

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)0.000
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: none
Teacher disagreement score0.082
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0150.002

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 head0.029
GPT teacher head0.214
Teacher spread0.186 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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