Notice bibliographique
Résumé
The article by Michael Leveridge and colleagues1 raises an issue that is not often addressed in the urology literature, and should provoke some discomfort and discussion. Every physician involved in resident training and evaluation is aware that, about 10 years ago, the Royal College redefined the goals of training beyond the acquisition of expertise in a specialty. Six additional roles were added to that of medical expert, including health advocate, communicator, collaborator, manager, scholar and professional. Resident evaluations now require the resident's performance in each of these areas to be determined on a regular basis. For residents working hard to master surgical and clinical skills and basic and clinical sciences, the challenge represented by the acquisition of expertise in these other 6 roles, and (perhaps even more critically) the need to demonstrate that the skill sets involved have been acquired, is large. One of these roles, the scholar (i.e., researcher), has been accepted for 100 years as an important one in surgery. Canadian residents are encouraged to obtain some research experience, and indeed this a requirement of some programs. However, it is likely that most urologists involved in resident training believe that the teaching involved in the 5 roles beyond medical expert and scholar occurs implicitly, by example, rather than by explicit instruction. We teach communication skills by being good communicators; we demonstrate collaborator skills by collaborating; and so on. The article by Leveridge and colleagues confirms that explicit training in health advocacy is rare in residency training and that active participation in health advocacy projects is virtually nonexistent. The Royal College presumably considers that this is a deficiency. But is it? Becoming a medical expert involves the acquisition of multiple skill sets. Five years of residency training after medical school is a short time to develop proficiency. Would formal training in the other 5 roles, beyond expert and scholar, represent a dilution of the focus on knowledge acquisition and clinical and surgical skills? Or would resident instruction and opportunity for involvement in, for example, health advocacy, raise the level of expertise achieved in other areas? Does this matter? We welcome our readers' views on this question. The Laval group continues their remarkable productivity in the area of cancer biomarkers. Stephan Bolduc and colleagues2 report that urinary prostate specific antigen (PSA), and particularly the urinary to serum PSA ratio, discriminate between benign prostatic hyperplasia and prostate cancer in men with mild PSA elevation. Urinary PSA is appealing because of its availability and low cost. It would have been interesting to know how urinary PSA performs compared with free versus total ratio, or to a multi-parameter nomogram approach incorporating other risk factors. We look forward to more evidence regarding the utility of this assay.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,014 | 0,042 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,009 | 0,010 |
| Communication savante | 0,008 | 0,008 |
| Science ouverte | 0,002 | 0,010 |
| Intégrité de la recherche | 0,019 | 0,018 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,016 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».