MétaCan
Menu
Back to cohort
Record W4409340716 · doi:10.56367/oag-046-11196

Lives and money: Understanding the true cost of sepsis in Canada

2025· article· en· W4409340716 on OpenAlex
Kali Barrett, Victoria Chechulina, Fatima Sheikh

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueOpen Access Government · 2025
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsWestern UniversityMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsEconomicsNatural resource economicsHistory

Abstract

fetched live from OpenAlex

Lives and money: Understanding the true cost of sepsis in Canada Kali Barrett, Victoria Chechulina, and Fatima Sheikh discuss the economic burden of sepsis in Canada and the economic rationale for implementing coordinated, national strategies to combat this often-overlooked disease. Sepsis is a global health threat, responsible for a significant burden of deaths and disability in all economies. In Canada, this challenge is being addressed in part by Sepsis Canada, a National Research Network funded by the Canadian Institutes of Health Research (CIHR). The network was established to build the research infrastructure needed to enhance our understanding of sepsis, identify effective interventions, and implement strategies to reduce the illness and death it causes. Previously, members of Sepsis Canada have underscored how robust research infrastructure is critical for driving innovation and supporting high-quality scientific studies. These efforts are also central to developing a cohesive National Action Plan against sepsis, an essential step for coordinating research, clinical care, and public health initiatives. (1)

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.109
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

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

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 head0.149
GPT teacher head0.398
Teacher spread0.250 · 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