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Record W4401368486 · doi:10.5737/2368807632446343298

Intégration à la pratique infirmière de l’évaluation des effets neurocognitifs à long terme de la thérapie par lymphocytes T à récepteur antigénique chimérique

2024· article· fr· W4401368486 on OpenAlexvenueno aff
Emma McArthur

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2024
Typearticle
Languagefr
FieldMedicine
TopicAutoimmune Neurological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsValuation (finance)HumanitiesPhilosophyPolitical scienceMedicineEconomics

Abstract

fetched live from OpenAlex

La thérapie par lymphocytes T à récepteur antigénique chimérique (CART) est un traitement récent aux effets neurotoxiques bien connus. Peu de recherches ont étudié les effets neurotoxiques à long terme, bien que certaines données aient été recueillies après le traitement chez quelques sous-ensembles de patients. Pour mesurer la progression des effets neurotoxiques, les infirmières peuvent évaluer l’état neurologique des patients avant et après la thérapie CARTT. Ces évaluations font appel à des outils subjectifs et objectifs, et exigent de bien comprendre les facteurs de risque associés à un degré élevé d’effets cognitifs indésirables. Les infirmières en hématologie peuvent agir pour répondre à ce besoin négligé en appliquant des mesures d’intervention et de suivi qui s’appuient sur la recherche actuelle, ce qui améliorera le devenir des patients. Mots-clés : thérapie par lymphocytes T à récepteur antigénique chimérique, évaluations infirmières, effets neurotoxiques

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.324
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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Same venueCanadian Oncology Nursing JournalSame topicAutoimmune Neurological Disorders and TreatmentsFrench-language works237,207