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Record W3042294867 · doi:10.1029/2020jf005553

Are Results in Geomorphology Reproducible?

2020· article· en· W3042294867 on OpenAlexafffund
Michael Church, Ashley Dudill, Jeremy G. Venditti, Philippe Frey

Bibliographic record

VenueJournal of Geophysical Research Earth Surface · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaInstitut National de Recherche en Sciences et Technologies pour l'Environnement et l'AgricultureAgence Nationale de la RechercheCanada Foundation for Innovation
KeywordsFlumeReplication (statistics)Repetition (rhetorical device)ReproductionEarth scienceReproducibilityComputer scienceGeologyGeomorphologyEcologyMathematicsBiologyStatisticsGeometryPhilosophyFlow (mathematics)

Abstract

fetched live from OpenAlex

Abstract There recently has arisen substantial concern for the reproducibility of scientific findings, but the discussion has not significantly impacted Earth science. We consider repetition, replication, and reproducibility in Earth science, using an example from geomorphology. Repetition repeats the program of observations in the same exercise to establish precision of results. Replication is duplication of observations using similar resources but in an independent program. Reproduction is confirmation of scientific principles using different resources in an independent program. We conclude that results will mainly be limited to reproduction—confirmation of principles—and that this is the essential goal for advancing the science. We illustrate these concepts by review of our experiments on the infiltration of fine grains in flowing water into a bed of coarser grains, conducted using glass beads in a laboratory flume.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.117
GPT teacher head0.328
Teacher spread0.211 · 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.

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

Citations13
Published2020
Admission routes2
Has abstractyes

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