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Regulation and execution of molecular disassembly and catabolism during senescence

2007· review· en· W2149460588 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNew Phytologist · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Gene Expression Analysis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSenescenceTranscriptomeCatabolismBiologyCell biologyCellular senescenceComputational biologyGeneticsGeneMetabolismBiochemistryGene expressionPhenotype

Abstract

fetched live from OpenAlex

Senescence is a highly orchestrated developmental stage in the life cycle of plants. The onset of senescence is tightly controlled by signaling cascades that initiate changes in gene expression and the synthesis of new proteins. This complement of new proteins includes hydrolytic enzymes capable of executing catabolism of macromolecules, which in turn sets in motion disassembly of membrane molecular matrices, leading to loss of cell function and, ultimately, complete breakdown of cellular ultrastructure. A distinguishing feature of senescence that sets it apart from other types of programmed cell death is the recovery of carbon and nitrogen from the dying tissue and their translocation to growing parts of the plant such as developing seeds. For this to be accomplished, the initiation of senescence and its execution have to be meticulously regulated. For example, the initiation of membrane disassembly has to be intricately linked with the recruitment of nutrients because their ensuing translocation out of the senescing tissue requires functional membranes. Molecular mechanisms underlying this linkage and its integration with the catabolism of macromolecules in senescing tissues are addressed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.844
Threshold uncertainty score0.881

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.317
Teacher spread0.292 · 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