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Record W4400059016 · doi:10.1667/rade-24-00018.1

“Lethal Mutations” a Misnomer or the Start of a Scientific Revolution?

2024· review· en· W4400059016 on OpenAlexaff
Carmel Mothersill, Rhea Desai, Colin Seymour, Marc S. Mendonca

Bibliographic record

VenueRadiation Research · 2024
Typereview
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMisnomerScientific revolutionMutationGeneticsBiologyEpistemologyPhilosophyGene

Abstract

fetched live from OpenAlex

The aim of this paper is to review the history surrounding the discovery of lethal mutations, later described as delayed reproductive death. Lethal mutations were suggested very early on, to be due to a generalised instability in a cell population and are considered now to be one of the first demonstrations of "radiation-induced genomic instability" which led later to the establishment of the field of "non-targeted effects." The phenomenon was first described by Seymour et al. in 1986 and was confirmed by Trott's group in Europe and by Little and colleagues in the United States before being extended by Mendonca et al. in 1989, who showed conclusively that the distinguishing feature of lethal mutation occurrence was that it happened suddenly after about 9-10 population doublings in progeny which had survived the original dose of ionizing radiation. However, many authors then suggested that in fact, lethal mutations were implicit in the original experiments by Puck and Marcus in 1956 and were described in the extensive work by Sinclair in 1964, who followed clonal progeny for up to a year after irradiation and described "small colony formation" as a persistent consequence of ionizing radiation exposure. In this paper, we examine the history from 1956 to the present using the period from 1986-1989 as an anchor point to reach into the past and to go forward through the evolution of the field of low dose radiobiology where non-targeted effects predominate.

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 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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.824
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.204
GPT teacher head0.515
Teacher spread0.311 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2024
Admission routes1
Has abstractyes

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