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Record W6903475697 · doi:10.11575/prism/35921

Applying A Resilience Lens To Shale Gas Development In Northeastern British Columbia

2015· other· en· W6903475697 on OpenAlexaboutno aff

Bibliographic record

VenuePRISM (University of Calgary) · 2015
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodDiafiltrationProteogenomicsTSG101Articular cartilage damage

Abstract

fetched live from OpenAlex

Shale gas development in northeastern British Columbia involves the interaction of complex social and ecological systems. This research applies the concept of specified resilience (sensu Walker and Salt 2012) to water resources within the Liard River basin affected by shale gas development. The resilience assessment begins with a summary of the major concepts integral to resilience thinking and then proceeds to describe the Social-Ecological System (SES) in terms of its ecology, governance, Aboriginal interests, industrial technology and practices. The system discussed in the research project highlights system states, controls and feedback relationships useful in evaluating resilience in response to shale gas development. Attributes contributing to resilience were selected to describe the current state of the SES allowing the author to make observations on possible management interventions. Resilience of the water resources in the study area was found to be greatly affected by the existing governance framework prompting the author to advocate a more pragmatic management approach.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.423

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0080.005
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.014
GPT teacher head0.195
Teacher spread0.181 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2015
Admission routes1
Has abstractyes

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