Notice bibliographique
Résumé
The good news has just been received from Clarivate that the CJA has received its first Impact Factor (IF)—0.6 over 2 years and 1.0 over 5 years. This metric is a measure of average citations received for published content. The articles in CJA about the Canadian experience with cannabis received the most citations in prominent journals in the field. This issue of the journal includes various articles of relevance to our practitioners. The first 2 articles are epidemiological analyses of risk factors for addiction. Tardelli et al analyze risk factors from weighted samples of respondents of the US Survey on Drug Use and Health from 2015 to 2019 (n = 214,415). Male sex, White ethnicity, and sexual minority identity predicted the use of most illegal substances. A welcome scoping review of articles published between 2015 and 2021, by Brabete et al, covers the existing evidence about a range of methamphetamine interventions. Twenty-four articles delve into the impact on outcomes between sex, gender, trauma, and equity factors. Not surprisingly, the need for tailored interventions focusing on more diverse populations is highlighted. The next contribution, from Nader et al, is a retrospective chart review of 121 patients receiving care at an innovative primary obstetrics program for high-risk inner-city pregnant patients with severe substance use disorders. Positive maternal and neonatal outcomes are associated with high rates of prenatal hospital attendance. A complementary case report from Hacker-Teper et al describes the rotating prescription to a pregnant patient from methadone to sublingual buprenorphine/naloxone via micro-dosing, followed by initiation of depot buprenorphine via macro-dosing immediately post-partum. In a preliminary study by Yeap et al, a sample of 20 people with cannabis use disorder was paired according to their tobacco co-use. Eleven used 10 cigarettes a day, while 9 used 5 or less cigarettes a day. The heavier users of cigarettes experienced higher levels of cannabis withdrawal severity, suggesting that targeting tobacco use may improve rates of cannabis cessation. Despite the current deadly opioid crisis, a comparison by Bassi et al at 11 teaching sites with a mandatory clinical rotation in addiction, in a residency program at the University of Toronto, elicited a structural marginalization of people with opioid use disorder and the need for focussed curricular changes to support their treatment. The wisdom of this recommendation is further supported by a complementary retrospective study of opioid-related drug toxicity deaths, by Whitten et al in Newfoundland and Labrador, where “accidental deaths, not intentional,” rather than “suicides” or “undetermined,” are the most prevalent manners of death. Last, but not least, it is also my particular pleasure to announce that CSAM has appointed Dr David Crockford, CJA’s current Deputy Editor, as the Journal’s next Editor-in-Chief, as I conclude 13 years in this role, after the CSAM Annual Meeting in Hamilton. Dr Crockford has been involved with the CJA from its inception and is eminently qualified to lead the journal into its next phase.
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 | 0,038 | 0,232 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,003 |
| Méta-épidémiologie (sens large) | 0,007 | 0,005 |
| Bibliométrie | 0,016 | 0,009 |
| Études des sciences et des technologies | 0,006 | 0,005 |
| Communication savante | 0,050 | 0,019 |
| Science ouverte | 0,007 | 0,008 |
| Intégrité de la recherche | 0,020 | 0,017 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,166 | 0,152 |
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 ».