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Record W6969401423 · doi:10.5683/sp3/otpolc

Data for: Differential structure and function of phosphorus-cycling microbial communities in organic and upper mineral soil horizons across a temperate rainforest chronosequence

2023· dataset· en· W6969401423 on OpenAlexaff

Bibliographic record

VenueBorealis · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsChronosequenceAbundance (ecology)Sampling (signal processing)Relative species abundanceBaySoil horizonMicrobial population biologyTopsoilHorizonCommunity structure

Abstract

fetched live from OpenAlex

Field campaign sampling dunes along the Big Bay chronosequence, on the west coast of New Zealand’s South Island at the mouth of the Awarua River (44.2988°S, 168.0672°E) in November 2018. Dunes with approximate ages of 300, 800 and 4000 yBP (i.e., corresponding to earthquake events in the years 1717, 1220 and ~4000 years ago; also referred as BBX1717, BBX1220 and BBX04) were chosen for detailed soil sampling. We paired analysis of soil properties with chemical and microbial analysis. We quantified P-cycling microbial communities using qPCR to estimate bacterial and fungal abundance and p-cycling genes and used high-throughput sequencing to estimate microbial community diversity. Data are from 3 dunes with four representative sampling locations. Each sampling point consisted of the removal of a block of soil 25 x 25 cm to a depth of ~25 cm to obtain both the organic horizon and mineral soil immediately beneath: n = 24.

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 score0.111
Threshold uncertainty score0.221

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0220.016

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 head0.030
GPT teacher head0.288
Teacher spread0.257 · 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
Published2023
Admission routes1
Has abstractyes

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