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Record W3192922703

DAM CATCHMENT RESTORATION EROSION PREVENTION AND RESPONSE

2021· article· en· W3192922703 on OpenAlexaff
Taylor Josephy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil erosion and sediment transport
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSpillwayWatershedErosionHydrology (agriculture)Erosion controlEnvironmental scienceWet seasonFlood mythDry seasonFlood controlWater resource managementGeographyGeologyGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

Siandwazi Village, located in southern Zambia, is a community of smallholder farmers who rely on a community dam for dry season water supply and food production. Gully erosion is occurring on the dam spillway and in its watershed due to the dam’s influence on stream gradient and agricultural land-conversion. A community-led, volunteer erosion control program was conducted throughout the 2019/20 rain season to protect the dam from erosion-derived failure and re-establish natural hydrological regimes. Erosion control efforts on the spillway reduced annual gully and rill erosion from 10.5 to 2m3/yr through the placement of rock, sand-filled sacs, and vetiver grass (Vetiveria zizanioides). Erosion prevention and control efforts in the watershed were planned but never proceeded due to labour constraints and drought-derived socioeconomic challenges, therefore erosion increased from 12 to 14.5m3/yr. Construction on a flood-mitigating check dam was initiated and a baseline run-off coefficient was established to allow for specific watershed objective-setting moving forwards into next rain season.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.028
GPT teacher head0.249
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 designObservational
Domainnot available
GenreEmpirical

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
Published2021
Admission routes1
Has abstractyes

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