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Record W2994828118 · doi:10.1080/24705357.2019.1680320

A case-study evaluating river rehabilitation alternatives and habitat heterogeneity using the hydromorphological index of diversity

2019· article· en· W2994828118 on OpenAlexaff
Walter Gostner, W. K. Annable, Anton Schleiss, M. Paternolli

Bibliographic record

VenueJournal of Ecohydraulics · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsHabitatEnvironmental scienceSpatial heterogeneityDiversity (politics)Diversity indexIndex (typography)Channel (broadcasting)Spatial variabilityHydrology (agriculture)Restoration ecologyEcologyComputer scienceGeologySpecies richnessStatisticsBiologyGeotechnical engineeringMathematics

Abstract

fetched live from OpenAlex

Concurrent rehabilitation alternatives were evaluated for a 1900 m reach of the River Etsch in northern Italy using a recently developed Hydro Morphological Index of Diversity (HMID) model. HMID is a new tool enabling quantitative assessments of river restoration alternatives on ecologically relevant scales. The model is able to characterize both the spatial and temporal hydrodynamic variability, in relation to morphological characteristics, and thereby to assess the overall physical habitat variability imparted by different restoration alternatives.Three habitat alternatives were evaluated (boulder clusters, groynes, alternating bars) and compared to existing conditions where a prismatic channel exists. The placement of boulder clusters represented the simplest and cheapest option to implement but produced marginal improvements in the aquatic habitat. Installation of groynes resulted in moderate increases to spatial habitat variability, resulting in the largest capital investment. The introduction of alternating bars within a modestly increased channel width produced the greatest increase in physical habitat diversity and thus morphodynamic complexity while resulting in moderate capital investment construction costs compared to a full geomorphic restoration. The alternating bar rehabilitation alternative also supported the greatest habitat diversity and lowest variation in hydraulic conditions under low-flow conditions.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.227

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.309
Teacher spread0.256 · 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 teacher head, 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

Citations9
Published2019
Admission routes1
Has abstractyes

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