MétaCan
Menu
Back to cohort
Record W2891073685 · doi:10.15441/ceem.17.269

Zero point survey: a multidisciplinary idea to STEP UP resuscitation effectiveness

2018· article· en· W2891073685 on OpenAlex
C. Reid, Peter G. Brindley, Chris Hicks, Simon Carley, Clare Richmond, Michael Lauria, Scott D. Weingart

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.

Bibliographic record

VenueClinical and Experimental Emergency Medicine · 2018
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsSt. Michael's HospitalUniversity of Alberta
Fundersnot available
KeywordsResuscitationMedicineCornerstonePoint (geometry)Zero (linguistics)Multidisciplinary teamMultidisciplinary approachSet (abstract data type)Medical emergencyEmergency medicineNursingComputer science

Abstract

fetched live from OpenAlex

The primary survey assessment is a cornerstone of resuscitation processes. The name itself implies that it is the first step in resuscitation. In this article, we argue that in an organized resuscitation the primary survey must be preceded by a series of steps to optimize safety and performance and set the stage for the execution of expert team behavior. Even in the most time critical situations, an effective team will optimize the environment, perform self-assessments of personal readiness and participate in a preemptive team brief. We call these processes the 'zero point survey' as it precedes the primary survey. This paper explains the rationale for the zero point survey and describes a structured approach designed to be suitable for all resuscitation situations.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.683
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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)0.0180.001

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 head0.129
GPT teacher head0.520
Teacher spread0.391 · 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