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Record W2037094271 · doi:10.5558/tfc78146-1

Assessment of relative environmental risk from logyard run-off in British Columbia

2002· article· en· W2037094271 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Forestry Chronicle · 2002
Typearticle
Languageen
FieldEngineering
TopicForest Biomass Utilization and Management
Canadian institutionsUniversity of British Columbia
FundersBC Hydro
KeywordsEnvironmental scienceRisk assessmentRelative riskRisk managementRisk analysis (engineering)GeographyStatisticsBusinessMathematicsComputer science

Abstract

fetched live from OpenAlex

Run-off is generated at logyards at sawmills and dryland sorts when mobile water interacts with woody debris. Logyard run-off can contain a range of constituents with the potential to have an adverse impact on the receiving environment. Many geoclimatic, operational and physical factors contribute to the volume and characteristics of run-off, and a management tool to predict relative environmental risk from different sites would be of value. In this study, we attempted to develop such a tool. A survey was devised and distributed to logyard operators in British Columbia. The survey provided information on site characteristics, volumes and types of wood processed, operational practices, the incidence of run-off, run-off treatment practices, as well as the ultimate receiving environment. Qualitative and quantitative data from the survey were subjected to statistical analyses to: (1) determine the factors that contributed to risk; (2) assign relative risk ratings to each site; and (3) rank facilities according to their potential to impact the receiving environment. Multidiscriminant analysis was used to determine which factors were correlated to environmental risk posed by run-off. Eighty-nine percent (64/72) of the facilities had visible run-off. Sixty-six percent (42/64) of the facilities fell into the high risk category with the remaining 34% (22/64) being low risk. In order of importance, volume of wood stored onsite (largest contribution), frequency of run-off events and colour intensity of run-off (smallest contribution) were factors that significantly contributed to risk and were correlated positively. The methods employed in this study could be applied as management tools to identify sites for further assessment and evaluate the need for remediation. Key words: wood leachate, run-off, logyard, dryland sort, environmental impact, toxic, remediation

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.999

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)0.0020.000

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 head0.195
Teacher spread0.188 · 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