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Record W2789920689 · doi:10.6028/nist.tn.1476

Performance of physical structures in Hurricane Katrina and Hurricane Rita :

2006· report· en· W2789920689 on OpenAlexaff
Stephen A. Cauffman

Bibliographic record

Venuenot available
Typereport
Languageen
FieldMaterials Science
TopicEngineering and Material Science Research
Canadian institutionsNational Research Council Canada
FundersFederal Highway AdministrationNational Institute of Standards and TechnologyCenters for Disease Control and PreventionElectric Power Research InstituteFederal Emergency Management AgencyU.S. Department of Homeland SecurityU.S. Department of Transportation
KeywordsHurricane katrinaEnvironmental scienceMeteorologyAtlantic hurricaneStormGeographyNatural disaster

Abstract

fetched live from OpenAlex

Certain commercial entities, equipment, products, or materials are identified in this report to describe data, observations, findings, and/or recommendations adequately or to trace the history of the procedures and practices used.Such identification is not intended to imply recommendation, endorsement, or implication that entities, products, materials, or equipment are necessarily the best available for this purpose.Nor does such identification imply a finding of fault or negligence by the National Institute of Standards and Technology. Disclaimer No. 2The policy of NIST is to use the International System of Units (metric units) in all publications.In this document, however, units are presented in metric units or the inch-pound system, whichever is prevalent in the discipline.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.057
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.300
Teacher spread0.283 · 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
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

Citations57
Published2006
Admission routes1
Has abstractyes

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