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Record W6948652354 · doi:10.5066/p9q1ti5e

Water column and sediment incubations to measure dissolved organic matter dynamics in the Fox rivermouth (Lake Michigan; 2016-2017)

2022· dataset· en· W6948652354 on OpenAlexaff

Bibliographic record

VenueUSGS DOI Tool Production Environment · 2022
Typedataset
Languageen
FieldMathematics
TopicMorphological variations and asymmetry
Canadian institutionsTrent University
Fundersnot available
KeywordsWater columnDissolved organic carbonSedimentNitrogenPhosphorusHydrology (agriculture)Flux (metallurgy)Sediment–water interfaceOrganic matter

Abstract

fetched live from OpenAlex

These data are associated with experiments performed in 2016 and 2017 in the Fox rivermouth (Green Bay, WI; Lake Michigan). Between the De Pere Dam and the Lake Michigan coastline, we performed experiments to measure water column transformation of dissolved organic matter (DOM) and sediment flux of DOM. These experiments consisted of incubations of surface water or intact sediment cores and repeated measures over time of DOM concentration and optical properties. When these experiments were performed, we also measured inorganic nitrogen and phosphorus dynamics. Results and data related to nitrogen and phosphorus have already been published. We also measured ancillary environmental data that would assist in understanding variation in DOM dynamics (e.g., incident solar radiation, water temperature, etc.). Using these data, we then modeled the overall change in DOM that is occurring in the Fox rivermouth.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.048
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.015

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 head0.019
GPT teacher head0.227
Teacher spread0.208 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

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