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Pediatric anesthetic meetings and conferences

2011· article· en· W1933447186 on OpenAlexaboutno aff
T. C. K. Brown

Bibliographic record

VenuePediatric Anesthesia · 2011
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFront (military)Library scienceFamily medicineGeography

Abstract

fetched live from OpenAlex

World Paediatric Anaesthetic meetings (held in relation to World Congress of Anesthesiologists) In 1984, David Steward (in Figure 1 , front row) and Seizo Iwai ( Figure 2 ) organized a meeting of pediatric anesthetists in Manila during the World Congress of Anesthesiologists. Following the meeting, there was a dinner at which John Zorab, then Secretary of the World Federation of Societies of Anaesthesiologists (WFSA), told the audience that if they wanted to set up a Paediatric Committee in the WFSA, they should request to do so immediately. A show of hands at this informal occasion showed a majority but not unanimous approval (because no aims and objectives had been defined for the committee). It was established at the WFSA Executive meeting the next day. Eventually, a multiauthored WFSA handbook on Pediatric Anesthesia, initiated by David Steward and finalized by Anneke Meursing, was produced some years later. Speakers at World Paediatric Anaesthesia Meeting in Melbourne, following the World Congress of Anesthesiologists in Sydney, April 1996. Front: M. Rawicz (Poland), C. Riquelme (Chile), A. Meursing #(the Netherland), D. Steward* (Canada); 2nd: C. Cote (USA), P. Limoges (Canada), G, Goresky* (Canada), F. Berry (USA); 3rd: C. da Silva(Brazil), P. Kempthorne (NZ), J. Moray (USA), D. Baines (Australia), F. Veckymans (Belgium); 4th: M. Yamashita, (Japan), P. Morris (UK), D. Hatch (UK), M. Marx (Uruguay), K. Brown* (Australia); 5th: S. Rajev (Russia), J. Overton (Australia), D. Pawar (India), I. Mackenzie (Australia). *Organized World Paediatric Anaesthetic meetings. #Organized 1st and 2nd FEAPA congresses. image Seizo (Jake) Iwai from Kobe, Japan. image

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)0.000
metaresearch head score (Gemma)0.000
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 score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.028
GPT teacher head0.234
Teacher spread0.206 · 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
Published2011
Admission routes1
Has abstractyes

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