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Record W2024392594 · doi:10.1080/15428110308984812

Report of the Howard Hughes Medical Institute's Workshop on the Performance of Laboratory Chemical Hoods

2003· article· en· W2024392594 on OpenAlexaff
Louis J. DiBerardinis, M.W. First, Esmeralda Party, Thomas C. Smith, Cheryl A. Warfield, Jenny Carpenter, Jason L. Cook, Douglas B. Walters, Michael R. Flynn, Edgar L. Galson, Pamela L. Greenley, Dale T. Hitchings, Gerhard W. Knutson, John Price, Janet S. Baum, Jeff D. Burton, Matthew D. Finucane, Daniel A. Ghidoni, Jerry Koenigsberg, Mark Lyons, Farhad Memarzadeh, David C. Norton, Glen Schuyler, Jon Zboralski, W. Emmett Barkley

Bibliographic record

VenueAIHA Journal · 2003
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsRowan Williams Davies & Irwin (Canada)
Fundersnot available
KeywordsStatement (logic)EngineeringTest (biology)Medical educationPsychologyOperations researchMedicineLawPolitical science

Abstract

fetched live from OpenAlex

The Howard Hughes Medical Institute sponsored a workshop on laboratory chemical hoods on June 8, 9, and 10, 1998, that brought together 24 experts in the field of laboratory chemical hoods to critically assess the information known about hood performance. Workshop participants developed 31 consensus statements that reflect their collective views on the body of knowledge or lack thereof, for laboratory chemical hoods. The consensus statements fall into four broad categories: (1) hood selection, use, and operation; (2) hood and laboratory design issues; (3) ventilation system design issues; and (4) hood performance testing. The consensus statements include 26 statements on what is known and unknown about the performance of laboratory chemical hoods, 2 statements of definition, and 3 statements that reflect the participants' agreement not to agree. The brief commentary that follows each consensus statement provides guidance and recommendations.

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)0.036
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0040.002
Open science0.0040.005
Research integrity0.0090.012
Insufficient payload (model declined to judge)0.0070.002

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 head0.078
GPT teacher head0.448
Teacher spread0.370 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations6
Published2003
Admission routes1
Has abstractyes

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