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Record W7065202311

Effects of a selection harvest in a riparian buffer situated in Manitoba Forest Management License 01

2001· other· en· W7065202311 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2001
Typeother
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsRiparian bufferRiparian zoneResource (disambiguation)Riparian forestBuffer stripRecreationSelection (genetic algorithm)
DOInot available

Abstract

fetched live from OpenAlex

Forest resource managers have become increasingly aware of the shortcomings of conventional riparian management. Riparian buffers may enter a decadent state as trees age and begin to acquire attributes that may reduce the effectiveness of the buffer and threaten non-timber resource values associated with the riparian zone. A selective harvest was designed and implemented in an experimental riparian buffer within FML 01, aimed at circumventing the problems associated with traditional riparian resource management. Due to the ecological and recreational value of the riparian resource, harvesting was designed with the intent to integrate various existing non-timber values. A pilot study was subsequently implemented to address the initial effects of selective harvesting on buffer floristics, the avian community, erosion and sedimentation and streamside aesthetics. Primary data was collected for one year prior to, and for one year following, harvesting. (Abstract shortened by UMI.)

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.007
GPT teacher head0.181
Teacher spread0.174 · 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

Citations0
Published2001
Admission routes1
Has abstractyes

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