MétaCan
Menu
Back to cohort
Record W2065408496 · doi:10.1017/s0317167100002043

Electronic Case-Report Forms of Symptoms and Impairments of Peripheral Neuropathy

2002· article· en· W2065408496 on OpenAlexvenueno aff
P. James B. Dyck, D. W. Turner, Jenny L. Davies, Peter C. O’Brien, Cynthia A. Rask

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2002
Typearticle
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsnot available
FundersGenentechNational Institute of Neurological Disorders and StrokeEli Lilly and Company
KeywordsMedicineClinical trialPeripheral neuropathyData entryAuditPatient recruitmentMedical recordPhysical therapyMedical physicsMedical emergencyDatabaseSurgeryComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVE: For the conduct of controlled clinical trials, epidemiologic surveys or even of medical practice of varieties of peripheral neuropathy, the usefulness, error rate and cost-effectiveness of scannable case-report forms has not been studied. MATERIALS AND METHODS: The overall performance, the frequency of the problems identified and corrected, and the time saved from use of a standard paper case report form was evaluated in multicenter treatment trials, single center epidemiologic surveys and in our neurologic practice. The paper case report form (Clinical Neuropathy Assessment [CNA]) for pen entry at study medical centers for patient, disease and demographic information (Lower Limb Function [LLF] and Neuropathy Impairment Score [NIS]) can be faxed to a core Reading and Quality Assurance Center where the form and data is electronically and interactively evaluated and corrected, if needed, by participating medical centers before electronic entry into database. OBSERVATIONS AND CONCLUSIONS: 1) The approach provides a standard, scannable paper case report form for pen entry of neuropathy symptoms, impairments and disability at the bedside or in the office which is retained as a source document at the participating medical center but a facsimile can be transferred instantaneously, its data can be programmed, interactively evaluated, modified and stored while maintaining an audit trail; 2) it allowed efficient and accurate reading, transfer, analysis, and storage of data of more than 15,000 forms used in multicenter trials; 3) in 500 consecutive CNA evaluations, software programs identified and facilitated interactive corrections of omissions, discrepancies, and disease and study inconsistencies, introducing only a few readily identified and corrected entry errors; and 4) use of programmed, as compared to non-programmed assessment, was more accurate than double keyboard entry of data and was approximately five times faster.

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)0.046
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: Other · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.046
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0340.008

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 head0.025
GPT teacher head0.287
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
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

Citations50
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicCancer Treatment and PharmacologyFrench-language works237,207