Notice bibliographique
Résumé
It seems every year we har about another disease that threatens our health. One of them happens to be a condition known as Lyme Disease. It's cause by a bacterium known as Borrelia and it can have some pretty nasty symptoms including fever, fatigue, and joint pain. Worse, it may have the ability to stick around and cause people years of pains ranging from arthritis to neurological and even heart problems. As for how it's spread, it comes from the bite of a tick. There's been an explosion of cases over the last decade and in some areas of the country, ticks have replaced mosquitoes as public health enemy #1.On this week's show, we take a closer look at the bacterium behind the disease and how to help you stay safe. Our first guest is an expert on this bacterium behind this disease. His name is George Chaconas and he is a professor at the University of Calgary. For years, he was a Canada Research Chair on the condition formally known as Lyme Borreliosis. We explore how the infection progresses in the body and manages to escape our immune system. We also get into the potential for resistance and long-term effects on the body.The bacterium is known as a spirochete, which means it looks like a corkscrew. This is similar to another bacterium that causes a more known illness, syphilis. We talk with Chaconas about the similarities between the two and how this may help us understand how we may be able to diagnose and possibly treat Lyme disease effectively.In our SASS Class, we find out how to avoid Lyme Disease through prevention. We talk with Katie Clow, a veterinarian and assistant professor at the University of Guelph. She's been studying how humans and pets can avoid getting bitten by a tick and shares her knowledge with us. Her tips will help you to stay safe when you're out enjoying the grassy and wooded areas. If you enjoy The Super Awesome Science Show, please take a minute to rate it on Apple Podcasts and be sure to tell a friend about the show. Thanks to you, we've been nominated for a Canadian Podcast Award as Outstanding Science and Medicine Series. Let's keep the awesome momentum going together! Twitter: @JATetroEmail: thegermguy@gmail.comGuests:George ChaconasWeb: https://www.ucalgary.ca/bprg/chaconasKatie ClowWeb: https://katieclow.com/ Twitter: @KatieClow1Learn more about your ad choices. Visit megaphone.fm/adchoices
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,757 | 0,163 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».