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Record W2922251981 · doi:10.2134/jeq2019.01.0001c

The Future of Humic Substances Research: Preface to a Debate

2019· article· en· W2922251981 on OpenAlexaff
H. H. Janzen

Bibliographic record

VenueJournal of Environmental Quality · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsCLARITYOrganic matterReading (process)Earth scienceEnvironmental scienceChemistryPolitical scienceEcologyGeologyBiologyLaw

Abstract

fetched live from OpenAlex

For centuries, scientists have been probing the nature and dynamics of organic matter in soil and sediment. A prominent approach in this research has been to extract using a strong alkaline solution. The continuing merits of this time-honored approach, however, has prompted some recent debate. Does the study of humic substances, as defined by alkaline extraction, still promise further advances in our understanding of organic matter dynamics in terrestrial and aquatic systems? The two articles in this special section offer divergent responses to this question, providing a framework for enlightening discourse that will help direct future research. Receptive reading of these views will not only lead to clarity on a crucial issue but also offer insight into how best to learn from potentially divisive questions that will inevitably arise in the study of soil, a still mysterious medium.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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)0.0010.000

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 head0.031
GPT teacher head0.323
Teacher spread0.291 · 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.

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

Citations17
Published2019
Admission routes1
Has abstractyes

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