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Record W2012749595 · doi:10.1136/ebn.11.4.111

Review: preprocedure information, breast cushions, and patient-controlled breast compression reduce mammography painCommentary

2008· letter· en· W2012749595 on OpenAlexaff
Phyllis Montgomery, Mike Conlon

Bibliographic record

VenueEvidence-Based Nursing · 2008
Typeletter
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsSudbury Regional HospitalLaurentian University
Fundersnot available
KeywordsMedicineCINAHLMammographyPsychological interventionBreast cancerMEDLINERandomized controlled trialPlaceboPhysical therapyBreast painMedical physicsAlternative medicineCancerNursingSurgeryInternal medicine

Abstract

fetched live from OpenAlex

D Miller Dr D Miller, University of Otago, Dunedin, New Zealand; dawn.miller@stonebow.otago.ac.nz How effective are interventions for reducing the pain of screening mammography? Studies selected compared interventions to reduce the pain or discomfort of screening mammography (eg, interventions preparing women before the mammogram, affecting staff or the physical environment of the screening facility, or altering aspects of the examination procedure) with placebo or usual care in women of any age. Outcomes were pain or discomfort of the procedure and image quality of the mammogram. Specialised Register of the Cochrane Breast Cancer Group, Medline, EMBASE/Excerpta Medica, and CINAHL (to 2006); and Current Controlled Trials and UK National Research Register (to …

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.539
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
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 head0.039
GPT teacher head0.311
Teacher spread0.272 · 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.

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
Published2008
Admission routes1
Has abstractyes

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