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Record W2142602148 · doi:10.1139/w05-098

Fertile sporophore production of <i>Typhula phacorrhiza</i> in the field is related to temperatures near freezing

2006· article· en· W2142602148 on OpenAlexafffundvenue
Yanqi Yang, Feng Chen, Tom Hsiang

Bibliographic record

VenueCanadian Journal of Microbiology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicTurfgrass Adaptation and Management
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaWashington State University
KeywordsHorticultureMoistureWater contentLimitingSowingBotanyBiologyAgronomyChemistryGeology

Abstract

fetched live from OpenAlex

Two field tests and one lab test were conducted to examine the environmental factors affecting sporophore production in Typhula phacorrhiza and to compare these results with those documented for T. ishikariensis and T. incarnata. In the 2001 lab test where lighting, soil moisture, and soil-sand media were tested in 50 mL screw-cap tubes incubated at 4 degrees C, the limiting factor for Typhula sporophore production was found to be moisture. In the fall 2001 field test, 100 sclerotia of six isolates from three Typhula spp. were placed into pots filled with a sand and soil mixture. The pots were monitored weekly, and maximum sporophore production for all six isolates and for watered and unwatered pots was observed at 11 weeks, which was soon after mean daily temperatures fell below 0 degrees C. In the second field test in fall 2003, five isolates of the three species were tested with similar procedures, but peak sporophore production was observed after 6 weeks, and again only after mean daily temperatures fell below 0 degrees C. In the field, sporophore production of T. phacorrhiza seems to require the same environmental cues as those of T. ishikariensis or T. incarnata, namely high moisture and temperatures near freezing.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.004
GPT teacher head0.189
Teacher spread0.186 · 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 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

Citations6
Published2006
Admission routes3
Has abstractyes

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