MétaCan
Menu
← Back to cohort
Record W4393815101 · doi:10.5281/zenodo.4291038

Phosphorus Content of Belwood Reservoir Sediment Core

2020· dataset· en· W4393815101 on OpenAlexaff
K. J. Van Meter, N. B. Basu, Rland Hall, Van Cappellen

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2020
Typedataset
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSediment corePhosphorusSedimentEnvironmental scienceContent (measure theory)Core (optical fiber)GeologyEnvironmental chemistryChemistryComputer scienceMathematicsGeomorphologyTelecommunications

Abstract

fetched live from OpenAlex

On February 14, 2018, four sediment cores were obtained from Belwood Lake, an approximately 7-km2 reservoir in the upper Grand River Watershed that was created in 1941 as a result of dam construction.Of these four, one core, , 8.7 cm internal diameter and 47 cm long, was selected for sediment core dating and laboratory analysis. Cores were collected using a Glew hammer-driven gravity corer fitted with a lucite tube and were subsequently transported to the lab, where they were sectioned at 0.5-cm intervals. Sediment samples were sealed in plastic bags and refrigerated at 4℃ until undergoing further analysis. One of the four cores collected (47 cm long), was selected for sediment core dating and laboratory analysis. In the laboratory, sequential loss-on-ignition (LOI) analysis was performed using ~0.5-g subsamples of wet sediment from each core slice, as described previously, to obtain the organic matter and carbonate content. The sediment P content of core slices was determined by IC-OES (Thermo Scientific iCAP 6300) after digestion with potassium persulfate-sulfuric acid . A sediment core chronology was developed based on gamma ray spectrometric determination of 210Pb activity at contiguous 0.5-cm intervals, using previously described methods.

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)0.001
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 score0.077
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.009

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 head0.055
GPT teacher head0.234
Teacher spread0.178 · 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicSoil and Water Nutrient Dynamics→French-language works237,207→