MétaCan
Menu
Back to cohort

Soil chemical properties and distribution of sclerotium grains in forest soils, Harz Mts., Germany

2004· article· en· W1970684703 on OpenAlexaff
Makiko Watanabe, Shunpei Ohishi, Angelika Pott, Ulrike Hardenbicker, K Aoki, Nobuo Sakagami, Hiroyuki Ohta, Nobuhide Fujitake

Bibliographic record

VenueSoil Science & Plant Nutrition · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsSclerotiumSoil waterChemistryBotanyPodzolHorticultureMineralogyAgronomySoil scienceBiologyGeology

Abstract

fetched live from OpenAlex

Relationships between the distribution of fungal sclerotium grains and soil chemical properties were studied in forest soils of Podsole, Braunfahlerde, and Braunerde-Podsoles in Harz Mts., Germany.Development of sclerotium grains was dominant in surface horizons (Ab, E horizons) within a 10-cm depth and weight density of grains ranged from 0.01 to 4.99 g kg-I soil.The SEM-EDX analysis proved that the weight percentage (excluding C and N) of AI 2 0 3 was 39.8-63.9%inside the grains.The content of elgosterol, a biomarker of viable fungal biomass, showed good correlations with weight density of sclerotium grains in grain-detected soils.The sclerotium grains were likely to be formed in soils with high ratios (>0.6) of organic bonding AI (~) to amorphous AI (AID), and with high contents of exchangeable AI (AI 3 +) (>0.54 g kg-I).The content and state of active AI were believed to be responsible for the development of sclerotium because sclerotium grains were not detected in acid soils which had lower levels of free colloidal AI (Aid' AID, AI p ) ' We believed that the intensive clay destruction associated with past lessivage process induced the absence of free colloid AI in such forest soils.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.427

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 head0.019
GPT teacher head0.195
Teacher spread0.176 · 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 designBench or experimental
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

Citations15
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueSoil Science & Plant NutritionSame topicMycorrhizal Fungi and Plant InteractionsFrench-language works237,207