Notice bibliographique
Résumé
As a child, I remember watching intently my pediatrician's steel stethoscope as it swung back and forth on his neck, like a hypnotist's pendulum, lulling me into a near-panicky dread of its cold metallic shock on my skin. Then, just before he placed it on my chest — I would brace myself, every single time — he would miraculously remember to warm it up with his hands. And all fear would be forgotten. Nowadays, technology has “progressed”: we do not have those cold stethoscopes any more. Instead, we have an armamentarium of much colder and darker things, like MRI machines, bronchoscopes and MRSA masks. Modern textbooks talk about things like blood samples, CT scans and MRIs as being “more dependable than the physical exam,” but that's not the point. These tests are the idioms of a modern medical jargon that patients simply do not speak. Their language is the language of the physical exam, however pointless it may seem to us at times. In a strange metaphorical way, I feel that it is now my duty to warm up the stethoscope, somehow, through explanation and shared concern, to lessen the cold shock of the unnatural devices and procedures we now use to help our patients. The first step in achieving this is to understand that our notion of what constitutes caring for the patient does not necessarily (and probably does not usually) coincide with the patient's idea of what it is to be cared for. Recently, I went to see a specialist for a recurrent problem that I have had for as long as I can remember. Roughly, our interaction went as follows: after we introduced ourselves to one another, I candidly told him exactly what the problem was, detailing it as any self-respecting medical student would. He acknowledged the problem and proceeded to ask me exactly how I would like things to be: essentially, what I thought he could do for me. After this, he took a moment to consider the problem, comb through the details and cut to the heart of the matter. He posed a few more questions and pondered further. Next, he offered his expert opinion and treatment plan and asked if I understood and agreed with his strategy. Finally, he proceeded with an extensive examination and the first treatment. Before I knew it, conversation was flowing freely, taking root in the frivolous banalities of small talk and blooming — an hour later — into the sharing of views and goals and, indeed, the sharing of many personal stories, as between friends. The power differential between the expert and his subject, and the disempowering act of sharing a personal concern with a stranger and putting myself “in his hands” seemed much easier now that the expert was also a person. Before I left that day, I scheduled another haircut in six weeks and wondered, “Why can't doctors be like that?”
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 | 0,002 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,002 |
| Communication savante | 0,008 | 0,008 |
| Science ouverte | 0,002 | 0,008 |
| Intégrité de la recherche | 0,008 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,471 | 0,203 |
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 ».