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Record W2328593598 · doi:10.5558/tfc2016-012

Southern Rockies Watershed Project

2016· article· en· W2328593598 on OpenAlexaffvenue
U. Silins, A. Anderson, Kevin D. Bladon, Monica B. Emelko, Micheal Stone, Sheena A. Spencer, C. Williams, Michael J. Wagner, Amanda M. Martens, Kirk Hawthorn

Bibliographic record

VenueThe Forestry Chronicle · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of WaterlooUniversity of Alberta
Fundersnot available
KeywordsWatershedBiogeochemistryDisturbance (geology)Drainage basinHydrology (agriculture)Environmental scienceResource (disambiguation)Structural basinEcologyGeographyGeologyGeomorphologyBiology

Abstract

fetched live from OpenAlex

The Southern Rockies Watershed Project was initiated in 2003 to describe the impacts of severe natural disturbance by wildfire on a broad range of headwaters, larger river basin scale, and downstream water resources (Phase I). This watershed research is unique in that trans-disciplinary linkages between hydrology, biogeochemistry, aquatic ecology, downstream river basin processes, implications for human water use, and economic implications are providing broad insights into wildfire effects on water. A second phase of the research (Phase II) focuses on evaluating the effects of several alternative forest harvesting practices on these same water resource “values”. Collectively, this research is providing comprehensive information on watershed function after forest disturbance in Rocky Mountain watersheds.

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)0.002
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.125
Threshold uncertainty score0.248

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0470.008

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 head0.009
GPT teacher head0.213
Teacher spread0.204 · 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

Citations11
Published2016
Admission routes2
Has abstractyes

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Same venueThe Forestry ChronicleSame topicFire effects on ecosystemsFrench-language works237,207