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Record W2109401305 · doi:10.1016/j.ijrobp.2014.04.003

In Regard to Girinsky et al

2014· letter· en· W2109401305 on OpenAlexaff
Gábor Gyenes

Bibliographic record

VenueInternational Journal of Radiation Oncology*Biology*Physics · 2014
Typeletter
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineAsymptomaticCoronary artery diseaseInternal medicineCardiologyTask forceRadiologyRevascularizationMyocardial infarction

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: aff_core · design weight: 5595.24 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: editorial/commentary
about Canada: no
confidence: low

Letter to the editor about a specific radiation oncology paper; no abstract, and the correspondence concerns a clinical study rather than research practice.

GPT-5.6 (high)T3 · adjacent, not in scope
genre: editorial/commentary
about Canada: no
confidence: high

A letter responding to another article is contextual scholarly communication.

Grok 4.5T3 · adjacent, not in scope
genre: editorial/commentary
about Canada: no
confidence: high

Letter to the editor responding to a clinical paper, contextual correspondence under the rubric.

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)0.002
metaresearch head score (Gemma)0.037
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.079
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0060.003
Open science0.0020.002
Research integrity0.0790.046
Insufficient payload (model declined to judge)0.0120.008

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 head0.021
GPT teacher head0.350
Teacher spread0.330 · 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
GenreCommentary

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
Published2014
Admission routes1
Has abstractno

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Same venueInternational Journal of Radiation Oncology*Biology*PhysicsSame topicCardiac Imaging and DiagnosticsFrench-language works237,207