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Record W2918585486 · doi:10.1080/09553002.2019.1589016

Targets, pools, shoulders, and communication – a reflection on the evolution of low-dose radiobiology

2019· review· en· W2918585486 on OpenAlexaff
Carmel Mothersill, Colin Seymour

Bibliographic record

VenueInternational Journal of Radiation Biology · 2019
Typereview
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsMcMaster University
Fundersnot available
KeywordsContext (archaeology)RadiobiologyMainstreamEpistemologyMisnomerIllusionReflection (computer programming)Paradigm shiftProcess (computing)PsychologyComputer scienceBiologyCognitive psychologyMedicinePolitical scienceRadiation therapyPhilosophy

Abstract

fetched live from OpenAlex

This reflection aims to look at the evolution of thinking about radiation dose response relationships from the early years of the journal when target theory prevailed to the present day when dose response is seen as a more holistic process involving multiple levels of organization and communication. The review is structured to consider how the old ideas evolved leading to apparently abrupt paradigm shifts. The odd data leading to these conceptual shifts are reviewed. Topics, which are currently still not mainstream are considered with a view to how they may change the future of radiobiology. Finally some personal reflections on the insights gained during the writing of the review are presented. The major conclusion from this study is that ideas concerning survival curves and radiation dose responses evolved and (epi)mutated gradually, driven in a large part by the techniques available for studying radiobiological processes. The illusion of abrupt paradigm shifts is not really borne out by the history when primary references are studied rather than textbooks or reviews. The textbooks necessarily simplify and distil complex data to provide a 'take-home message' while reviews are usually very personal collations selected among the vast amount of scientific literature. Primary references reveal the context of the discussion and the caveats and uncertainties of the authors.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.980
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.044
GPT teacher head0.388
Teacher spread0.344 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations22
Published2019
Admission routes1
Has abstractyes

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