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Record W4408525517 · doi:10.5539/sar.v14n1p36

Enhancement of Organic Carbon Formation in Pumice Sand with QBLOCK™. Second Part

2025· article· en· W4408525517 on OpenAlexvenueno aff
Arturo Solís Herrera, María del Carmen Arias Esparza

Bibliographic record

VenueSustainable Agriculture Research · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPumiceTotal organic carbonCarbon fibersEnvironmental scienceAgronomySoil scienceGeologyChemistryGeochemistryEnvironmental chemistryMaterials scienceBiology

Abstract

fetched live from OpenAlex

Soil fertility is a challenge to overcome since the beginning of time. Soil fertility is one of the main constraints that limits agricultural food production by smallholder farmers and astronauts. The value of soil chemical measurements using as indicators Soil organic carbon (SOC), total nitrogen (N), phosphorus availability and pH are often-suggested chemical parameters. Fertility problems cannot be treated in isolation and must include rotations, fallow practices, use of crop residues and use of nutrient inputs. Soil fertility is fundamental for food security. It is ultimately determined by the geology in the area, but also greatly affected by soil management and nutrient input. Soon, it will be necessary to develop food sources for future astronauts living and operating deep space. It is fundamental to plant growth researchers working to unlock agricultural innovations that could help us understand how plants might overcome stressful conditions in food-scarce areas here on Earth and eventually apply it to complex conditions like lunar surface environment.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.013
GPT teacher head0.248
Teacher spread0.234 · 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
Published2025
Admission routes1
Has abstractyes

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