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Record W6927071565 · doi:10.25573/serc.12252005

Dataset: Carbon data for intertidal soils and sediments, Skeena River estuary, British Columbia

2020· dataset· en· W6927071565 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2020
Typedataset
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsnot available
Fundersnot available
KeywordsTransectSoil waterHydrology (agriculture)EstuaryVegetation (pathology)Intertidal zoneSalt marshSampling (signal processing)

Abstract

fetched live from OpenAlex

Tidal marsh soils were sampled at low tide along 12 transects along the Skeena River estuary south of Port Edward, British Columbia, in 2014 and 2017. Eight of the transects were on the northeast side of the channel; four were on the southwest side. Sampling locations were stratified according to vegetation type. Usually three pits were excavated to 1 m depth on each transect, with one pit in each of the distinct vegetation zones. Bulk samples were collected from each distinct soil horizon, or where horizons were not clearly differentiated, at 25 cm depth intervals. Core samples of fixed volume were also collected from the same excavations for bulk density determination. Chemical analyses consisted of total C concentration (equivalent to organic C for these non-calcareous materials), total N, pH, and electrical conductivity (a measure of salinity).

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)0.004
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 score0.237
Threshold uncertainty score0.477

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.012
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0330.029

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 head0.045
GPT teacher head0.274
Teacher spread0.230 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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