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Record W4384701476 · doi:10.1016/j.softx.2023.101469

FIPEX v10.4: An ArcGIS Desktop Add-in for assessing impacts of fish passage barriers and longitudinal connectivity of rivers

2023· article· en· W4384701476 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSoftwareX · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsParks CanadaMemorial University of NewfoundlandUniversity of British ColumbiaFisheries and Oceans Canada
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of CanadaDalhousie UniversityParks Canada
KeywordsBiomeComputer scienceFish <Actinopterygii>Environmental scienceEnvironmental resource managementHydrology (agriculture)Water resource managementEcologyFisheryEcosystemGeology

Abstract

fetched live from OpenAlex

FIPEX v10.4 is designed to decrease the time required to assess the individual and cumulative effects of river barriers to fish passage and to assess river connectivity from headwaters to outflow (i.e., longitudinal connectivity) Loss of longitudinal connectivity due to anthropogenic barriers is a global problem contributing to unprecedented biodiversity loss in freshwater biomes. Yet, assessing longitudinal connectivity from the perspective of fish and prioritizing ecological restoration is challenging without specialized tools. The Fish Passage Extension (FIPEX) v10.4 is designed to bridge network analysis and Geographic Information System (GIS) in support of river connectivity assessments. It is developed as an open source VB.NET ‘Add-In’ for ArcGIS Desktop (v10.4+) with an option to run R statistical software scripts to calculate the Dendritic Connectivity Index (DCI).

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.020
GPT teacher head0.274
Teacher spread0.253 · 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