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Record W3089106845 · doi:10.1080/24705357.2020.1813057

How to strengthen interdisciplinarity in ecohydraulics? Outcomes from ISE 2018

2020· article· en· W3089106845 on OpenAlexaff
Roser Casas‐Mulet, Davide Vanzo, Ana Adeva‐Bustos, Camille J. Macnaughton, Michael J. Stewardson, G. B. Pasternack, Eva C. Enders, Fiona Dyer

Bibliographic record

VenueJournal of Ecohydraulics · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsField (mathematics)ConversationFace (sociological concept)Engineering ethicsPolitical sciencePublic relationsInterdisciplinaritySociologyKnowledge managementSocial scienceComputer scienceEngineering

Abstract

fetched live from OpenAlex

Interdisciplinary approaches are required to tackle complex environmental issues as freshwater ecosystems face unprecedented pressures globally. The emerging Ecohydraulics field of research should, therefore, take steps towards developing true interdisciplinarity to adapt to a continuing changing world. This study contributes to the ongoing discussion on interdisciplinarity in Ecohydraulics and shapes its growth by identifying key actions, actors and implementation strategies that can strengthen it. Based on an online questionnaire and a workshop involving over 150 early and established careers, we present a list of 20 prioritised actions that will help engage the research community towards specific goals and will result in increased interdisciplinary outcomes. While early career researchers (ECRs) have taken the lead on creating this roadmap, its implementation should be a joint responsibility of both ECRs, established career scientists, groups, and institutions within Ecohydraulics. The list of identified actions and assigned responsibility should, therefore, be considered a conversation starter. Continued revision of the here-stated approaches will be required in the future as the field of research and its community progresses. With this contribution, we resume a critical reflection on where the Ecohydraulics field of research and community stand today and suggest where resources should be invested in the long-term to consolidate the inherent interdisciplinarity in Ecohydraulics.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.682

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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.247
Teacher spread0.215 · 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 teacher head, 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

Citations2
Published2020
Admission routes1
Has abstractyes

Explore more

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