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Record W2917559146 · doi:10.3390/w11020366

Biological Diversity in Headwater Streams

2019· article· en· W2917559146 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

VenueWater · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSTREAMSHabitatEcologyEcosystemPopulationFreshwater ecosystemEnvironmental scienceAquatic ecosystemWatershedStewardship (theology)GeographyBiologyComputer science

Abstract

fetched live from OpenAlex

Headwaters, the sources of all stream networks, provide habitats that are unique from other freshwater environments and are used by a specialised subset of aquatic species. The features of headwaters that provide special habitats include predator-free or competitor-free spaces; specific resources (particularly detrital based); and moderate variations in flows, temperature and discharge. Headwaters provide key habitats for all or some life stages for a large number of species across just about all freshwater phyla and divisions. Some features of headwaters, including isolation and small population sizes, have allowed for the evolutionary radiation of many groups of organisms within and beyond those habitats. As small and easily engineered physical spaces, headwaters are easily degraded by streambank development, ditching and even burial. Headwater streams are among the most sensitive of freshwater ecosystems due to their intimate linkage with their catchments and how easily they are impacted. As a unique ecosystem with many specialist species, headwater streams deserve better stewardship.

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 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.991

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.010

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 head0.015
GPT teacher head0.192
Teacher spread0.177 · 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