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Record W4401489167 · doi:10.21203/rs.3.rs-4725658/v1

Management of Adult Sepsis in Resource-Limited Settings: Global Expert Consensus Statements Using a Delphi Method

2024· preprint· en· W4401489167 on OpenAlexaff
Louise Thwaites, Prashant Nasa, Brett Abbenbroek, Vu Quoc Dat, Simon Finfer, Arthur Kwizera, Lowell Ling, Suzana M Lobo, Robert Sinto, Dita Aditianingsih, Massimo Antonelli, Yaseen M. Arabi, Andrew C. Argent, Luciano César Pontes Azevedo, Elizabeth Bennett, Arunaloke Chakrabarti, Kevin De Asis, Jan J. De Waele, Jigeeshu Vasishtha Divatia, Elisa Estenssoro, Laura Evans, Abul Faiz, Naomi Hammond, Madiha Hashmi, Shevin T. Jacob, Jimba Jatsho, Yash Javeri, Karima Khalid, Lie Khie Chen, Mitchell M. Levy, Ganbold Lundeg, Flávia Ribeiro Machado, Yatin Mehta, Mervyn Mer, Do Ngoc Son, Gustavo A. Ospina‐Tascón, Marlies Ostermann, Chairat Permpikul, Hallie C. Prescott, Konrad Reinhart, Gloria Rodriguez Vega, Halima S-Kabara, Gentle Sunder Shrestha, Wangari Siika, Toh Leong Tan, Subhash Todi, Swagata Tripathy, Bala Venkatesh, Jean‐Louis Vincent, Sheila Nainan Myatra

Bibliographic record

VenueResearch Square · 2024
Typepreprint
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsDelphi methodDelphiResource (disambiguation)Computer scienceKnowledge managementEnvironmental resource managementMedicineEconomicsArtificial intelligence

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.202
metaresearch head score (Gemma)0.187
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.984

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2020.187
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.003
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0020.008
Research integrity0.0020.002
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 head0.109
GPT teacher head0.519
Teacher spread0.410 · 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.

Study designQualitative
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
Published2024
Admission routes1
Has abstractno

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