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Record W7033530800

Roster of State Officials, 2014

2014· other· en· W7033530800 on OpenAlexfundno aff

Bibliographic record

VenueIowa Publications Online (State Library of Iowa) · 2014
Typeother
Languageen
FieldImmunology and Microbiology
TopicPoxvirus research and outbreaks
Canadian institutionsnot available
FundersUnited States Drug Enforcement AdministrationVlaamse regeringNatural Resources Conservation ServiceLOEWE Zentrum AdRIAYale UniversityU.S. Department of Veterans AffairsStrongUniversity of PittsburghIowa Pork Producers AssociationIowa State UniversityU.S. Department of Homeland SecurityCorporation for National and Community ServiceGoddard Space Flight CenterJohns Hopkins UniversityU.S. Department of JusticeEli Lilly and CompanyIowa Department of TransportationCollege of Agriculture and Life Sciences, Iowa State UniversityIowa Soybean AssociationU.S. Department of Health and Human ServicesUniversity of Northern IowaIowa Energy CenterU.S. Army Corps of EngineersU.S. Department of TransportationMcGill UniversityU.S. Department of Commerce
KeywordsState (computer science)Field (mathematics)Government (linguistics)Key (lock)Work (physics)
DOInot available

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.496
Threshold uncertainty score0.708

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.5040.335

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 head0.014
GPT teacher head0.264
Teacher spread0.249 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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

Citations0
Published2014
Admission routes1
Has abstractno

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