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Record W2345137157 · doi:10.1080/07347332.2016.1181133

Prospective memory impairment in chemotherapy-exposed early breast cancer survivors: Preliminary evidence from a clinical test

2016· article· en· W2345137157 on OpenAlexaff
Marc Bedard, Shailendra Verma, Barbara Collins, Xinni Song, Lise Paquet

Bibliographic record

VenueJournal of Psychosocial Oncology · 2016
Typearticle
Languageen
FieldPsychology
TopicCognitive Functions and Memory
Canadian institutionsOttawa HospitalCarleton University
Fundersnot available
KeywordsProspective memoryBreast cancerProspective cohort studyCognitionCognitive impairmentMedicineOncologyClinical psychologyPsychologyCancerInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

We report the results of a secondary analysis of a cross-sectional study (Paquet et al., 2013 Paquet, L., Collins, B., Song, X., Chinneck, A., Bedard, M., & Verma, S. (2013). A pilot study of prospective memory functioning in early breast cancer survivors. Breast, 22 (4), 455–461.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) to evaluate the cognitive operations involved in prospective memory (PM) deficits exhibited by chemotherapy-exposed breast cancer (BC) survivors. PM was assessed with the memory for intentions screening test administered to 80 patients and 80 healthy controls. Patients performed worse than controls on the PM tasks and had more “omission” errors (indices of the prospective component of the tasks) than the controls. No group differences emerged on a recognition test. Although further studies will be needed to disentangle the multiple cognitive operations involved in PM, these findings are consistent with the notion that self-initiated retrieval processes rather than encoding are implicated in PM impairment among BC survivors.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.047
GPT teacher head0.404
Teacher spread0.357 · 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

Citations20
Published2016
Admission routes1
Has abstractyes

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Same venueJournal of Psychosocial OncologySame topicCognitive Functions and MemoryFrench-language works237,207