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Record W2291519838 · doi:10.19044/esj.2016.v12n5p386

Determinación De Áreas De Inundación En El Municipio De Chia- Colombia Mediante Hec-Ras En La Cuenca Baja Del Río Frio

2016· article· en· W2291519838 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Scientific Journal ESJ · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Resource Management and Quality
Canadian institutionsImpact
Fundersnot available
KeywordsFloodplainFlooding (psychology)Structural basinGeographyDrainage basinHydrology (agriculture)Environmental scienceGeomorphologyGeologyCartography

Abstract

fetched live from OpenAlex

The phenomenon La Niña caused flooding in Colombia during 2010 and 2011, especially in the upper basin of the Bogota River, this natural risk has produced major property damage and a decrease in socio-economic conditions in major urban and rural centers. For that reason, this paper presents a determination of the floodplain of the lower basin of the Rio Frio in the urban area of Chia Colombia by HEC RAS. The model allowed to determine the maximum water levels reached on the floodplain of the Rio Frio as it passes through the urban area of Chia, for return periods of rainfall of 2.33, 5, 10, 25, 50 and 100 years. Finally recommendations for the planning of the municipality in terms of these areas found are made.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.011
GPT teacher head0.253
Teacher spread0.242 · 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