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Record W2930700235 · doi:10.1016/j.carj.2019.03.002

Recommendations for the Management of the Incidental Renal Mass in Adults: Endorsement and Adaptation of the 2017 ACR Incidental Findings Committee White Paper by the Canadian Association of Radiologists Incidental Findings Working Group

2019· article· en· W2930700235 on OpenAlexaffabout
Iain D. C. Kirkpatrick, Gary Brahm, Gevork N. Mnatzakanian, Casey Hurrell, Brian R. Herts, Jeffery R. Bird

Bibliographic record

VenueCanadian Association of Radiologists Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsUniversity of SaskatchewanUniversity of TorontoWestern UniversityUniversity of Manitoba
FundersSiemens Healthineers
KeywordsMedicineAssociation (psychology)White (mutation)Adaptation (eye)Renal massWhite paperFamily medicineInternal medicineKidneyLaw

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

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)0.024
metaresearch head score (Gemma)0.135
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: Other · Consensus signal: none
Teacher disagreement score0.993
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.135
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0040.003
Science and technology studies0.0040.004
Scholarly communication0.0060.004
Open science0.0060.004
Research integrity0.0270.030
Insufficient payload (model declined to judge)0.0080.007

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 head0.020
GPT teacher head0.242
Teacher spread0.222 · 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
GenreOther

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

Citations14
Published2019
Admission routes2
Has abstractno

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