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Record W4241972853 · doi:10.5194/essd-2018-126-ac1

Author responses to referee comments on “Fifty years of recorded hillslope runoff on seasonally-frozen ground: The Swift Current, Saskatchewan, Canada dataset” by Anna E. Coles et al.

2019· peer-review· en· W4241972853 on OpenAlexaboutno aff
Anna Coles

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsSwiftCurrent (fluid)Surface runoffGeographyHydrology (agriculture)FisheryEnvironmental scienceOceanographyGeologyEcologyBiologyGeotechnical engineeringPhysics

Abstract

fetched live from OpenAlex

SpenceRC1.1 In this paper, the authors summarize a hydrological and chemistry dataset from a set of experimental hillslopes in Saskatchewan, Canada.It is a very nice dataset, which deserves to be catalogued and preserved.Its value is certainly enhanced by the long period of record.The data are easily accessible from Government of Canada open data websites.Upon reading the paper, I felt like there should be more description of the data, and more information on the methods used to collect it.As it is now, the paper does not provide enough information, particularly of the latter, for new users of the data to maximize its usage.My comments, both major and minor, are below.AC1.1 Thank you for your comments.We couldn't agree more that this dataset deserves to be preserved and used for future studies.We agree in hindsight that there should have been more information on methods and descriptive statistics of the data.We respond to your individual comments pertaining to this and other aspects, below.MC1.1 We have edited the revised manuscript to address all of your comments.Specific changes detailed below.RC1.2 Page 1 Line 10: perhaps say "nutrient flux (or concentration or export)" AC1.1 Agreed.MC1.1 Edited to "nutrient concentrations" RC1.3 Page 1 Line 13: Perhaps pick one of "edge of field" or "hillslope" and stick with it throughout the paper.AC1.2 Agreed.MC1.2There was one occurrence of "edge-offield" and one of "field" in the manuscript.Changed these to "hillslope" to be consistent with the rest of the manuscript.RC1.4 Page 1: Line 20: The digital elevation data that are mentioned here should be introduced earlier in the abstract.AC1.4 Agreed.MC1.4 Added a line earlier in the abstract to say that digital elevation data are available for the three hillslopes at a 2 m resolution, and also at a 0.25 m resolution for one of the hillslopes (Hillslope 2) C2 ESSDD Interactive

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)0.008
metaresearch head score (Gemma)0.118
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.966

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.118
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.011
Science and technology studies0.0030.001
Scholarly communication0.0040.002
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.3230.157

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 head0.118
GPT teacher head0.349
Teacher spread0.231 · 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.

Study designNot applicable
DomainEvaluation
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
Published2019
Admission routes1
Has abstractno

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