MétaCan
Menu
Back to cohort
Record W4230227283 · doi:10.1177/120347540400800205

Early Detection of Skin Cancer by Family Physicians: A Pilot Project

2004· article· en· W4230227283 on OpenAlexaff
Gillian C. de Gannes, Janet L. Ip, Magdalena Martinka, Richard I. Crawford, Jason K. Rivers

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2004
Typearticle
Languageen
FieldMedicine
TopicCutaneous Melanoma Detection and Management
Canadian institutionsSKiN HealthSt. Paul's HospitalVancouver Hospital and Health Sciences CentreUniversity of British Columbia
Fundersnot available
KeywordsMedicineSkin cancerIntervention (counseling)CancerIncidence (geometry)Randomized controlled trialBiopsyProspective cohort studySkin biopsyDermatologySurgeryPathologyInternal medicineNursing

Abstract

fetched live from OpenAlex

Background: Malignant melanoma is rising quickly in incidence and mortality rates. Family physicians (FPs) have been reported to lack confidence in diagnosing skin cancers. Objective: The aim of this study was to determine whether an educational intervention can improve FPs' abilities to diagnose skin cancers. Methods: The design was a prospective, randomized trial which included a skin cancer questionnaire, a video intervention, and a skin biopsy review. Results: Pre-intervention, FPs answered 57% of the questions correctly on the skin cancer questionnaire. Post-intervention, the video intervention group scored higher than did the control group. The video intervention group removed 10% fewer benign lesions and almost 3 times more malignant lesions compared with their pre-intervention biopsy rate. No findings were statistically significant. Conclusion: An educational intervention may improve FPs' knowledge and diagnosis of skin cancer. Our results may guide future studies with larger sample sizes in developing a skin cancer continuing medical education (CME) course for FPs.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.559
Threshold uncertainty score0.503

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.273
Teacher spread0.248 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations15
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cutaneous Medicine and SurgerySame topicCutaneous Melanoma Detection and ManagementFrench-language works237,207