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Record W4285494587 · doi:10.1021/acs.est.2c04163

Why Indoor Chemistry Matters: A National Academies Consensus Report

2022· article· en· W4285494587 on OpenAlexaff
Rima Habre, David C. Dorman, Jonathan P. D. Abbatt, William P. Bahnfleth, Ellison Carter, Delphine K. Farmer, Gillian Gawne-Mittelstaedt, Allen H. Goldstein, Vicki H. Grassian, Glenn Morrison, Jordan Peccia, Dustin Poppendieck, Kimberly A. Prather, Manabu Shiraiwa, Heather M. Stapleton, Meredith Williams, Megan E. Harries

Bibliographic record

VenueEnvironmental Science & Technology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsUniversity of Toronto
FundersNational Institute of Environmental Health SciencesCenters for Disease Control and PreventionEnvironmental Protection AgencyAlfred P. Sloan Foundation
KeywordsChapelLibrary scienceArchaeologyEnvironmental ethicsHistoryArt historyPhilosophy

Abstract

fetched live from OpenAlex

Author(s): Habre, Rima; Dorman, David C; Abbatt, Jonathan; Bahnfleth, William P; Carter, Ellison; Farmer, Delphine; Gawne-Mittelstaedt, Gillian; Goldstein, Allen H; Grassian, Vicki H; Morrison, Glenn; Peccia, Jordan; Poppendieck, Dustin; Prather, Kimberly A; Shiraiwa, Manabu; Stapleton, Heather M; Williams, Meredith; Harries, Megan E

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)0.077
metaresearch head score (Gemma)0.111
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 score0.077
Threshold uncertainty score0.408

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0770.111
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0050.006
Science and technology studies0.0040.004
Scholarly communication0.0080.007
Open science0.0060.008
Research integrity0.0150.017
Insufficient payload (model declined to judge)0.0100.003

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 head0.008
GPT teacher head0.228
Teacher spread0.220 · 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

Citations33
Published2022
Admission routes1
Has abstractyes

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