Notice bibliographique
Résumé
As doctors, none of us chose medicine because we enjoy dealing with human mortality. We chose medicine to be healers, comforters, figures of hope; we chose medicine because we want to save lives. At the start of my medical school career, I was not naïve enough to imagine that I would never be the bearer of bad news, never witness pain, chronic illness, or death. However, I never anticipated that death would become a daily part of my life or that we, as physicians, would be so incredibly undertrained in the frequent challenge of dealing with the frailty, morbidity, and mortality of life. I clearly remember the first time that one of my patients passed away. It was my first rotation of third year during my first shift in surgery. I had grabbed my resident and run upstairs to address a case of unexpected acute respiratory failure. Once there, we quickly realized that this patient would not make it through the night. He was a 92-year-old with terminal cancer, who had already been made a DNR. Although we ordered the standard labs and imaging, we knew the inevitable outcome; we called the family in, and, while waiting for them to arrive, he passed away. The senior resident and I were reviewing the chest X-ray and filling out the necessary paperwork when the family arrived, out of breath and disheveled as it was nearly 2:00 AM. This image is forever ingrained in my memory, and, even now, it causes me pain. Ironically, it is not the face of the patient, nor his death, that troubles me, but the faces of his family. While they had expected the eventual death of their father, they did not have the opportunity to say goodbye; he had passed away only minutes before their arrival. Later that same evening, the senior resident and I discussed his death with the junior resident. I was still visibly upset, and the junior resident noticed. He told me, “If you can’t handle death and you’re upset about stuff like this, then you should not be in medicine.” I fumed that if this was the junior resident’s callous approach to death, then he had no place in medicine. As physicians, we often fall short when it comes to handling death and dealing with its outcomes. Death is something that we haven’t been prepared for, something that we haven’t been taught, and something that, hopefully, few of us have had a lot of experience with. One would think that the longer you stayed in medicine, the easier dealing with death would get. I find that this is not the case. I never find death easy, and the faces of the patients whom I lose remain with me. I hope that I never stop remembering the families of my patients. These are the memories that remind me why we try so hard, why we do everything that we can, and why it is so important to take those few seconds to give patients and families a chance to say their goodbyes. In some cases, we will wish we had done things differently; in others, we will help families and patients toward a “good” death. In the end, at the end, what matters most are not the tests that were ordered, the surgeries that were performed, or any excuses for the circumstances, valid or invalid. Rather, it is the time that we spend with our patients and the small comfort that we can provide in those crucial moments. Death—whether imminent or likely—is one of the most terrifying moments for our patients and their families. When death beckons me, I hope that I will have a physician who remembers me, who spends those few extra moments with my family, helping them through one of life’s biggest challenges.
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 | 0,005 | 0,042 |
| 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 | 0,009 | 0,007 |
| Communication savante | 0,009 | 0,013 |
| Science ouverte | 0,002 | 0,008 |
| Intégrité de la recherche | 0,008 | 0,021 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,138 | 0,144 |
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 ».