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Interfertility between North American and European strains of <i>Phlebiopsis gigantea</i>

2005· article· en· W2067442870 on OpenAlexaboutno aff
R. Grillo, Jarkko Hantula, Kari Korhonen

Bibliographic record

VenueForest Pathology · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsGiganteaBiologyHeterokaryonSporeBotanyGeneticsGene

Abstract

fetched live from OpenAlex

Summary Thirteen homokaryotic strains of Phlebiopsis gigantea from Canada, six strains from the US and 10 strains from Europe were paired in all possible combinations in order to determine the degree of interfertility between them. The diagnosis of interfertility was based on the production of heterokaryotic fruit bodies in the pairings. Among the resulting 406 pairings, 253 (62%) fruited. Within the strains originating from Canada, USA and Europe, 64, 80 and 64% of the pairings fruited, respectively. The fruiting frequency in pairings between the Canadian and US strains was 65%, between the Canadian and European strains 55%, and between the US and European strains 67%. True hybridization between the European and North American P. gigantea was shown by analysing the single‐spore progeny using DNA fingerprinting. In spite of the relatively low interfertility in pairings within and between continents, no clear indication of the existence of intersterility groups was found. The low interfertility is probably due to the ageing of the pure cultures and to deficient fruiting ability of certain heterokaryons on agar medium. The results strongly suggest that although the North American and European strains of P. gigantea show some differentiation they can be regarded as belonging to the same biological species.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

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 science0.0000.001
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 head0.009
GPT teacher head0.224
Teacher spread0.215 · 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 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

Citations10
Published2005
Admission routes1
Has abstractyes

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