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Record W2189434492 · doi:10.21000/jasmr14010041

IMPACT OF SEED EXPOSURE TO PLANT MATERIAL ON PLANT GROWTH AND DEVELOPMENT ON REMEDIATED ARID LANDS

2014· article· en· W2189434492 on OpenAlexaff
Conrad W. Nelson, Adrian Unc, Kevin Lombard, Mary E. Lucero, Steven R. Perkins

Bibliographic record

VenueJournal American Society of Mining and Reclamation · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and fungal interactions
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsEnvironmental remediationTopsoilAridLand reclamationEnvironmental scienceRevegetationNative plantPlant communityPlant growthPlant speciesAgronomyEcologyBiologySoil waterContaminationEcological successionSoil scienceIntroduced species

Abstract

fetched live from OpenAlex

Remediation of land following surface mining requires the reestablishment of critical soil, plant, and microbial interactions on which the longterm sustainability of the site hinges. Current surface mine remediation practices may utilize topsoil with or without shredded plant material to overlay spoil. We evaluated whether the presence of such plant material may affect initial plant fitness and thus plant establishment. Tests were carried out in a greenhouse under controlled, replicated conditions common during early stages of remediation. Responses to seed exposure to plant material were species dependent. Plant growth parameters were linked to properties associated with the seed hull and seed surface and to functions associated with shredded plant material added to topsoil. Confirming the nature of these properties, hypothesized as microbial in origin, will be important for understanding factors critical to reclamation and management of disturbed sites, where native biological functions have been suppressed or fragmented. In degraded arid environments, such functions may govern micro-scale interactions that influence macro-scale processes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.912
Threshold uncertainty score0.117

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.234
Teacher spread0.214 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2014
Admission routes1
Has abstractyes

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