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Record W2028129038 · doi:10.1088/0952-4746/22/3a/304

Nonlinear dose response relationships and inducible cellular defence mechanisms

2002· article· en· W2028129038 on OpenAlexaff
Helmut Sch llnberger, Ron E. J. Mitchel, Douglas Crawford‐Brown, W. Hofmann

Bibliographic record

VenueJournal of Radiological Protection · 2002
Typearticle
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsHomologous recombinationDNAIrradiationBiophysicsComputational biologyDNA repairTransformation (genetics)Biological systemCell biologyIn vitroBiologyHomologous chromosomeSet (abstract data type)Plateau (mathematics)RadiationGeneChemistryComputer sciencePhysicsGeneticsMathematics

Abstract

fetched live from OpenAlex

With the inclusion of inducible radioprotective mechanisms in a radiobiological state-vector model it was possible to explain plateaus in dose-response relationships for neoplastic transformation produced by in vitro irradiation of different cell lines with low-LET irradiation at high dose rates. The current study repeated the simulation of one data set that contains a plateau at mid doses. In contrast to earlier studies, the new one did not model the repair of double-strand breaks (DSBs) located in bulk DNA (likely via non-homologous end joining) as being inducible. Repair of specific DSBs located in actively transcribed genes was assumed to occur via homologous recombination and was considered to be inducible. This reduced the number of parameters that have to be determined by fitting the model to data. In addition, all types of radical scavengers were formerly considered to be inducible by radiation. This was redefined in the current work and the effectiveness of scavengers was implemented in a refined way. The current work investigated whether these and other model adjustments lead to an improved fit of the data set.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.439

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.063
GPT teacher head0.260
Teacher spread0.197 · 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 designBench or experimental
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

Citations8
Published2002
Admission routes1
Has abstractyes

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