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THE ASSESSMENT OF TECK'S CASTLE PROJECT BASED ON FIVE VALUED ECOSYSTEM COMPONENTS

2021· article· en· W3161435978 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInterConf · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Quality and Pollution
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsEcosystemWater qualityEnvironmental scienceVegetation (pathology)CoalEnvironmental resource managementCoal miningPollutionEnvironmental planningEnvironmental protectionWater resource managementGeographyEcology

Abstract

fetched live from OpenAlex

Teck's Castle Project is the largest coal mine project to be mined in Canada. This article is an environmental assessment of Teck's Castle Project based on five valued ecosystem components (VECs) including: Surface Water Quality, Fish and Fish habitat, Vegetation, Local Employment, and Land Use. I proposed to use a surface water quality model to detect the degree of pollution of the water quality of the surrounding rivers and use an economic multiplier to measure the impact on local economic employment. Through research, I found that the water treatment facilities used by Teck Coal Limited can effectively alleviate the impact of the project on the water quality of the surrounding rivers, and I recommended that Teck Coal Limited wear protective equipment to protect their health when working.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.831

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)0.0010.000

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 head0.030
GPT teacher head0.302
Teacher spread0.271 · 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