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Record W4317040340 · doi:10.5751/es-13749-280105

Recovery or continued resuscitation? A clinical diagnosis of Colorado River sub-basin recovery programs

2023· article· en· W4317040340 on OpenAlexvenueno aff
Jaishri Srinivasan, Michael Schoon

Bibliographic record

VenueEcology and Society · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsAdaptabilityArchitectureEnvironmental resource managementEndangered speciesPsychological resilienceEcological successionResilience (materials science)Flexibility (engineering)EcologyEnvironmental scienceComputer scienceGeographyHabitatBiologyMathematicsStatistics

Abstract

fetched live from OpenAlex

With a particular emphasis on the Upper Colorado River Endangered Fish Recovery Program (UCR-EFRP) and Lower Colorado River Multi-Species Conservation Program (LCR-MSCP), we analyze, for each program, four system properties that contribute to resilience: system architecture, which includes (1) connectivity and distribution and (2) assemblage of system elements; and system dynamics, which includes (3) social and natural capital flows and (4) system renewal and continuation. Each of these system properties is analyzed based on specific social and corresponding biophysical indicators. The system properties were ranked on a carefully constructed scale based on gradations of each system property (derived from the literature) on both social and biophysical indicator standing. Our results indicate that the UCR-EFRP has relatively better social architecture and dynamics with relatively less impact on the ecological architecture and dynamics compared to the LCR-MSCP, though this result may be a function of the greater amount of infrastructural constriction and path dependence in the lower basin compared to the upper basin. We conclude by suggesting that a transformative pathway forward needs greater adaptability and flexibility incorporated into the social architecture and dynamics to move toward better ecological health of the river.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.298
Teacher spread0.273 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

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