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Record W2021168283 · doi:10.3390/en4091258

Tools for Small Hydropower Plant Resource Planning and Development: A Review of Technology and Applications

2011· review· en· W2021168283 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEnergies · 2011
Typereview
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsnot available
Fundersnot available
KeywordsHydropowerSmall hydroGeographic information systemResource (disambiguation)Identification (biology)SoftwareSpatial analysisScale (ratio)Computer scienceEnvironmental resource managementEnvironmental scienceEngineeringRemote sensingGeographyCartography

Abstract

fetched live from OpenAlex

This paper reviews and compares software tools for the planning and design of small hydropower (SHP) plants. The main emphasis is on small scale hydropower resource assessment computer tools and methodologies for the development of SHP plants corresponding to a preliminary or prefeasibility study level. The paper presents a brief evaluation of the historic software tools and the current tools used in the small hydro industry. The reviewed tools vary from simple initial estimates to quite sophisticated software. The integration of assessment tools into Geographic Information System (GIS) environments has led to a leap forward in the strengthening of the evaluation of the power potential of water streams in the case of the spatial variability of different factors affecting stream power. A number of countries (e.g., Canada, Italy, Norway, Scotland and the US) have re-assessed their hydropower capacities based on spatial information of their water stream catchments, developing tools for automated hydro-site identification and deploying GIS-based tools, so-called Atlases, of small-scale hydropower resources on the Internet. However, a reliable assessment of real SHP site feasibility implies some “on the ground” surveying, but this traditional assessment can be greatly facilitated using GIS techniques that involve the spatial variability of catchment characteristics.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.047
GPT teacher head0.249
Teacher spread0.203 · 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