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Record W3046306825 · doi:10.1139/cjfas-2020-0039

The River Continuum Concept: lessons from the past and perspectives for the future

2020· article· en· W3046306825 on OpenAlexvenueaboutno aff
Alberto Doretto, Elena Piano, Courtney E. Larson

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRiver ecosystemEcologyContext (archaeology)BiodiversityMetacommunityEcosystemGeographyEnvironmental resource managementEnvironmental scienceSociologyBiologyPopulationBiological dispersal

Abstract

fetched live from OpenAlex

The River Continuum Concept (RCC) is a milestone in stream ecology because of its comprehensive evaluation of the structure and function of lotic ecosystems. Linking stream physical and geomorphological attributes with patterns in biodiversity, functional traits, and metabolism dynamics, this theory describes downstream gradients in community composition and ecosystem processes. The aim of this review is to evaluate how the RCC, 40 years from its publication in the Canadian Journal of Fisheries and Aquatic Sciences, has influenced basic and applied research in stream ecology, focusing on the most important contributions and recent developments. This work puts into perspective the historical importance of the RCC in the scientific process and integrates past and recent theories, including metacommunity and metaecosystem theories and the river network perspective, to predict taxonomic and functional diversity of benthic communities. Thus, this review provides a unifying overview of the historical context of the field for exploring basic and applied ecological questions to the next generation of stream ecologists.

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)0.009
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0020.018
Scholarly communication0.0070.019
Open science0.0020.003
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0050.001

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 head0.213
Teacher spread0.192 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations173
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicFish Ecology and Management StudiesFrench-language works237,207