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Record W7100001442

Development and the Red River Corridor CONTRIBUTORS

2015· article· en· W7100001442 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemistry
TopicChemical synthesis and alkaloids
Canadian institutionsnot available
Fundersnot available
KeywordsSewagePopulationSustainable developmentHuman settlementAquiferSanitary sewerDevelopment plan
DOInot available

Abstract

fetched live from OpenAlex

The area between Winnipeg and Selkirk along the Red River is home to over 46,000 people living in 4000 homes which use private wells for drinking water, and septic systems for sewage treatment. This corridor, including the five municipalities of Selkirk, East St. Paul, West St. Paul, St. Andrews and St. Clements surround the Red River which empties into Lake Win-nipeg. These municipalities have acknowledged a growing environmental and public health risk of the increasing population and high use of private wells and septic systems along this water body, and the aquifer and came together to form the Red River Infrastructure Committee (RRIC). Concurrently, Selkirk is framing its draft development plan around these same princi-ples. The municipalities are attempting to address this growing sewage and water quality problem through the planning, placement, and management of sewage treatment systems, and the direction of new develop-ment to piped areas. Sewage treatment and piped service can be used as a planning tool to direct and support development according to comprehensive plans, to protect environ-mentally sensitive areas, and as an integrated part of an overall sustainable development system. The Selkirk Draft Development Plan and this inter-municipal co-operation through sewage treatment represent cutting edge practice in regional planning.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.599
Threshold uncertainty score0.797

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.001

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 head0.020
GPT teacher head0.210
Teacher spread0.191 · 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 designNot applicable
Domainnot available
GenreOther

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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