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Record W2047322112 · doi:10.1017/s0266462303000606

KEEPING CANCER GUIDELINES CURRENT: RESULTS OF A COMPREHENSIVE PROSPECTIVE LITERATURE MONITORING STRATEGY FOR TWENTY CLINICAL PRACTICE GUIDELINES

2003· article· en· W2047322112 on OpenAlex
Mary Johnston, Melissa Brouwers, George P. Browman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Technology Assessment in Health Care · 2003
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsHamilton Regional Laboratory Medicine ProgramMcMaster University
Fundersnot available
KeywordsMEDLINEGuidelineCochrane LibraryMedicineSystematic reviewProtocol (science)Evidence-based medicineScope (computer science)Family medicineAlternative medicineComputer sciencePathologyPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: To describe a methodology used to keep practice guidelines up to date and to summarize data collected during the first year of implementing this plan with a cancer practice guidelines program. METHODS: The updating strategy includes regular searches of peer-reviewed literature and meeting proceedings, review and interpretation of new evidence, review and revision of clinical recommendations, and notification to practitioners and policy makers about new evidence and its impact on recommendations. RESULTS: Eighty pieces of new evidence were found relating to seventeen of the twenty guidelines included in this study. On average, four pieces of new evidence were found per guideline, but there was considerable variation across the guidelines. Of the eighty pieces, nineteen contributed to modifications of clinical recommendations in six practice guidelines, whereas the remaining evidence served to support the original recommendations. None of the modifications led to changes that advised against original recommendations. MEDLINE, the Cochrane Library, and meeting proceedings yielded many pieces of evidence, whereas CancerLit and HealthStar did not contribute significantly to the overall yield. Furthermore, key pieces of evidence that led to modifications to the recommendations were often identified by members of the disease site groups before appearing in electronic databases. CONCLUSIONS: The updating process is resource intensive but yields important findings. In response to this evaluation, the updating protocol has been revised such that literature searches are conducted quarterly and the scope of sources searched routinely is restricted to MEDLINE, the Cochrane Library, and meeting proceedings.

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.

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)0.003
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.712
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.350
GPT teacher head0.658
Teacher spread0.308 · 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