MétaCan
Menu
Back to cohort
Record W3126789655 · doi:10.20383/101.0292

Hydrometeorological observations at three boreal forest sites (aspen, jack pine, and black spruce) located in central Saskatchewan, Canada

2020· article· en· W3126789655 on OpenAlexaboutno aff
Hafiz Faizan Ahmed, Warren Helgason, Alan Barr, T. A. Black

Bibliographic record

VenueOpen MIND · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceBlack spruceSnowBorealTaigaHydrometeorologySnowpackEvapotranspirationAtmospheric sciencesPrecipitationClimatologyMeteorologyGeographyEcologyForestryGeology

Abstract

fetched live from OpenAlex

Long-term observations are presented here from two coniferous (jack pine and black spruce) and one deciduous (aspen) forest sites located in central Saskatchewan, Canada. These sites were initiated through the Boreal Ecosystem and Atmosphere Study (BOREAS) program during 1994-96 (http://boreas.gsfc.nasa.gov/) and were later operated under the Boreal Ecosystem Research and Monitoring Sites (BERMS) program. All three sites were equipped with rich instrumentation that include walk-up scaffold towers fitted with sensors to measure air temperature, humidity and wind speed, above canopy shortwave and longwave radiation components, as well as fluxes of energy, carbon and water. Other onsite measurements included precipitation, snow depth, snow density, snow temperature, soil temperature and moisture profiles. These observations are useful for an improved understanding about the contrasts among sites. Moreover, the data is also very useful for modelling applications (calibration and validation). In addition to site observations, dynamically downscaled future meteorological observations by the Weather Research Forecast (WRF) model using Pseudo Global Warming (PGW) approach are included in the dataset. The WRF data was biased corrected by quantile-mapping method using the observed dataset. Thus, the data is ideal for testing, development, calibration, improvement, and validation of hydrological and/or land surface models as well as for projecting future changes in critical processes under changing climate.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.997

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)0.0040.000

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 head0.059
GPT teacher head0.229
Teacher spread0.170 · 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.

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

Citations2
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueOpen MINDSame topicCryospheric studies and observationsFrench-language works237,207