MétaCan
Menu
Back to cohort
Record W1999351853 · doi:10.1002/hyp.7075

Assessing factors that influence spatial variations in duff moisture

2008· article· en· W1999351853 on OpenAlexaff
L. D. Raaflaub, Caterina Valeo

Bibliographic record

VenueHydrological Processes · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCanopyEnvironmental scienceMoistureInterceptionWater contentTree canopyAtmospheric sciencesHydrology (agriculture)Spatial variabilityEcologyGeographyMeteorologyGeologyMathematics

Abstract

fetched live from OpenAlex

Abstract Patterns and spatial variations in the moisture of the decomposing organic matter on the forest floor (the duff) of a montane forest were analysed in an effort to determine the primary factors shaping these patterns. Above and below canopy meteorological conditions were monitored to determine the influence of canopy cover on duff moisture. The spatial and temporal distributions of duff moisture were assessed through daily duff moisture measurements collected at regular intervals in ten 10 × 10 m plots representing a variety of canopy types and densities. Meteorological conditions ranged from very wet to very dry and resulted in duff moisture variations that were more pronounced during wet periods than in extended periods of drying. Investigations on the influence of canopy type, tree density, and tree proximity on duff moisture patterns indicated that canopy type and tree proximity are the most important factors affecting duff moisture. Interception seems to be the primary controller of duff moisture patterns with an influence at the centimetre scale. Copyright © 2008 John Wiley & Sons, Ltd.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.360

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 communication0.0000.001
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 head0.022
GPT teacher head0.232
Teacher spread0.210 · 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.

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

Citations16
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueHydrological ProcessesSame topicPlant Water Relations and Carbon DynamicsFrench-language works237,207