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Record W34677273 · doi:10.3390/curroncol28050355

Aseguramiento de la calidad en programas de obtención de sistemas de armas

2010· article· en· W34677273 on OpenAlexfundno aff
Francisco Antón Brage

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2010
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety in Workplaces
Canadian institutionsnot available
FundersMichael Smith Health Research BC
KeywordsPolitical scienceMedicinePhilosophy

Abstract

fetched live from OpenAlex

Colorectal cancer (CRC) can be demanding for primary caregivers; yet, there is insufficient evidence describing the caregiver-reported outcomes (CROs) that matter most to caregivers. CROs refer to caregivers' assessments of their own health status as a result of supporting a patient. The study purpose was to describe the emotions that were most impactful to caregivers of patients with CRC, and how the importance caregivers attribute to these emotions changed from diagnosis throughout treatment. Guided by qualitative Interpretive Description, we analyzed 25 caregiver and 37 CRC patient interviews, either as individuals or as caregiver-patient dyads (six interviews), using inductive coding and constant comparative techniques. We found that the emotional aspect of caring for a patient with CRC was at the heart of caregiving. Caregiver experiences that engendered emotions of consequence included: (1) facing the patient's life-changing diagnosis and an uncertain future, (2) needing to be with the patient throughout the never-ending nightmare of treatment, (3) bearing witness to patient suffering, (4) being worn down by unrelenting caregiver responsibilities, (5) navigating their relationship, and (6) enduring unwanted change. The broad range of emotions important to caregivers contributes to comprehensive foundational evidence for future conceptualization and the use of CROs.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.283
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.384
Teacher spread0.368 · 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 teacher head, not a consensus.

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
Published2010
Admission routes1
Has abstractyes

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