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Record W4386519488 · doi:10.3389/fpls.2023.1281902

Editorial: Plant programmed cell death revisited, volume II

2023· editorial· en· W4386519488 on OpenAlexaff
Joanna Kacprzyk, Arunika H. L. A. N. Gunawardena, François Bouteau, Paul F. McCabe

Bibliographic record

VenueFrontiers in Plant Science · 2023
Typeeditorial
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to water stress
Canadian institutionsDalhousie University
Fundersnot available
KeywordsProgrammed cell deathAbiotic componentBiologyPlant developmentBiotechnologyComputational biologyBotanyEcologyGeneticsApoptosisGene

Abstract

fetched live from OpenAlex

Programmed cell death (PCD) is a fundamental process in plants, involved in plant development and mediating abiotic and biotic environmental interactions (Kacprzyk et al., 2011, Locato & De Gara, 2018). While our understanding of genetic regulation of plant PCD, and the sequence of molecular events involved, is still relatively fragmented, the potential of PCD research to inform development of future-proofed crop cultivars is increasingly recognized. This Research Topic compiles valuable contributions that highlight the increasing momentum of this research area, and reports the use of a diversity of approaches for studying cell death in plants.

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)0.004
metaresearch head score (Gemma)0.016
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.001
Science and technology studies0.0030.002
Scholarly communication0.0070.005
Open science0.0030.002
Research integrity0.0130.015
Insufficient payload (model declined to judge)0.0150.013

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 head0.010
GPT teacher head0.214
Teacher spread0.204 · 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
GenreEditorial

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

Citations0
Published2023
Admission routes1
Has abstractyes

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