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Limitations of TR-55 Curve Numbers for Urban Development Applications: Critical Review and Potential Strategies for Moving Forward

2020· article· en· W3003973475 on OpenAlexaff
Lindell Ormsbee, Steven Hoagland, Kyle Peterson

Bibliographic record

VenueJournal of Hydrologic Engineering · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsSpeculationRelevance (law)Editorial boardAudience measurementOperations researchComputer scienceEngineering ethicsRegional scienceManagement scienceData sciencePositive economicsPolitical scienceSociologyLibrary scienceEconomicsEngineeringLawFinance

Abstract

fetched live from OpenAlex

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal.

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)0.178
metaresearch head score (Gemma)0.453
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.178
Threshold uncertainty score0.939

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1780.453
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0110.009
Science and technology studies0.0020.004
Scholarly communication0.0090.011
Open science0.0060.003
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0040.002

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 head0.037
GPT teacher head0.258
Teacher spread0.221 · 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
GenreReview

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

Citations16
Published2020
Admission routes1
Has abstractyes

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