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I. Preparing for a Physiological Air War: Survey No. 1 by the Committee on Aviation Medicine of Aero Medical Research Facilities Available in America (12 Nov – 1 Dec 1940)

2017· article· en· W4389024986 on OpenAlexaboutno aff
Jay B. Dean

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsnot available
FundersUniversity of South Florida
KeywordsAviationAeronauticsWrightGovernment (linguistics)Library scienceWorld War IIManagementPolitical scienceMedicineEngineeringLaw

Abstract

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At its first meeting, 23 Oct 1940, the Committee on Aviation Medicine (CAM) was tasked with making “…a survey of the present status of the medical and physiological problems pertaining to aviation…[and to] advise regarding the correlation and coordination of such research undertakings as are going forward in various government labs and flying fields, as well as in civilian labs and commercial aviation units. In addition the Committee should suggest the inauguration and development of new studies and investigative projects pertaining to the biological aspects of aviation and necessary to the national defense.” The CAM was comprised of Dr. E.F. DuBois, CAM Chairman (Cornell U) and members Drs. C.K. Drinker (Harvard U), J.F. Fulton (Yale U), W.R. Miles (Yale U) and E.M. Landis (U Va). The CAM and two USN liaison officers (Cdr. J.R. Poppen, Capt. L.E. Griffis) traveled by air from Washington D.C. to eight sites during 12 Nov – 1 Dec 1940: Langley Field; Norfolk Naval Air Base; Guantanamo Bay, Cuba and the Aircraft Carriers Wasp & Ranger; the Pensacola Naval Air Station and School of Aviation Medicine; San Diego Naval Air Base, and the Carrier Saratoga; Wright Field, Aero Medical Research Unit, Dayton; and the Banting Institute and Eglinton Labs, Toronto, Canada. The CAM's report to the National Research Council (NAS Archives: CAM Bulletin, pp. 52–96) made 20 recommendations to improve preparedness for a high‐altitude, high‐speed air war. They recognized that to date, aero medical research had lagged far behind development of aircraft. The limiting factor in flight operations was the pilot's physiology. Larger and better labs were needed at Wright Field, Randolph Field, Pensacola and Washington. Aero medical research should be expedited in civilian labs through immediate federal funding. Research projects the CAM deemed of urgent importance included: development of a suitable O 2 breathing apparatus and pressurized aircraft cabins, with more studies in altitude chambers and planes at high‐altitude; mitigation strategies for relief from flyer's aeroembolism and black‐out from G‐forces during acceleration; effects of anoxemia on production of cerebral edema and increased cerebrospinal fluid pressure; effects of protracted breathing of 100% O 2 ; psychological tests; fatigue; critical assessment of the Schneider test as a predictor of human efficiency; usefulness of the EEG in aviation medicine; studies of visual problems; problems of adequate clothing, particularly electrically‐heated clothing; and general studies of recreational and rest facilities at air stations. By 1942, the CAM had expanded into 7 subcommittees to oversee America's growing aero medical research program: Advisory Commission A (on the west coast near aircraft factories) to the CAM in Washington, Acceleration, Oxygen & Anoxia, Decompression Sickness, Visual Problems, Clothing, and Motion Sickness. Other general fields included adrenal physiology, the crash project, explosive decompression and pressure‐cabin aircraft, flying fatigue, injury to flying personnel by anti‐aircraft blasts, first aid aloft, rehabilitation program, and problem of securing information from operation squadrons. Support or Funding Information USF

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 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)0.006
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.006
Science and technology studies0.0030.001
Scholarly communication0.0040.004
Open science0.0020.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0170.015

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 head0.110
GPT teacher head0.385
Teacher spread0.274 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2017
Admission routes1
Has abstractyes

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