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Record W2165743731 · doi:10.1007/s12245-010-0252-2

Towards systemic sustainable performance of TBI care systems: emergency leadership frontiers

2010· article· en· W2165743731 on OpenAlexaffabout

Bibliographic record

VenueInternational Journal of Emergency Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsContext (archaeology)MedicineTransformational leadershipSustainabilityMedical emergencyPublic relationsNursingPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Traumatic brain injuries (TBIs) continue as a twenty-first century subterranean and almost invisible scourge internationally. TBI care systems provide a safety net for survival, recovery, and reintegration into social communities from this scourge, particularly in Canada, the European Union, and the USA. AIMS: This paper examines the underlying issues of systemic performance and sustainability of TBI care systems, in the light of decreasing care resources and increasing demands for services. METHODS: This paper reviews the extant literature on TBI care systems, systems reengineering, and emergency leadership literature. RESULTS: This paper presents a seven care layer paradigm, which forms the essence of systemic performance in the care of patients with TBIs. It also identifies five key strategic drivers that hold promise for the future systemic sustainability of TBI care systems. CONCLUSIONS: Transformational leadership and engagement from the international emergency medical community is the key to generating positive change. The sustainability/performance care framework is relevant and pertinent for consideration internationally and in the context of other emergency medical populations.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.097
GPT teacher head0.380
Teacher spread0.283 · 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

Citations7
Published2010
Admission routes2
Has abstractyes

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