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Excess relative risk (ERR) estimates from the A-bomb survivors and from selected studies of persons exposed to protracted low-LET external ionizing radiation.

2015· dataset· en· W6904317938 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2015
Typedataset
Languageen
FieldSocial Sciences
TopicNational Identity and Symbolism
Canadian institutionsnot available
Fundersnot available
KeywordsRelative riskConfidence intervalLifetime riskIonizing radiationRisk assessmentInternal dose

Abstract

fetched live from OpenAlex

* Doses are external colon dose in mGy for Mayak workers, weighted colon dose in mGy for the atomic bomb survivors, Hp(10) in mSv for the 15-country and NRRW studies.(Hp(10) is the equivalent dose at a tissue depth of 10 mm beneath a dosimeter); stomach dose in mGy for the Techa river cohort † 90% confidence intervals used for comparison with published results in the 15-country and NRRW studies †† weighted average with weights of 0.75 for men and 0.25 for women to reflect the sex ratio in the Mayak worker cohort ‡ These populations are predominantly male § The estimate presented here is based on the 15-country study results withwith the Canadian data excluded ([29], page 405).). This estimate was used because of concerns about the Canadian data usedused in that study. This concerns have beenbeen supported by the recently published re-analysis of the Canadian workerworker data given in [34]. The ERR/SvSv estimate for using all of the 15-country data is 0.59 (95% CI <0 to 1.5, [29], page 403). ** There was no evidence that risk differed by sex in this cohort. Excess relative risk (ERR) estimates from the A-bomb survivors and from selected studies of persons exposed to protracted low-LET external ionizing radiation.

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)0.013
metaresearch head score (Gemma)0.028
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: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.078
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0050.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.087
GPT teacher head0.348
Teacher spread0.262 · 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
GenreDataset

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
Published2015
Admission routes1
Has abstractyes

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