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Unrooted Maximum Likelihood phylogenetic analysis of the concatenated SCAR-MLST dataset.

2015· other· en· W6960396368 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2015
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Research and Chemistry
Canadian institutionsnot available
Fundersnot available
KeywordsPhylogenetic treeAmazon rainforestOutbreakGenotypeHaplotypeCoalescent theoryLineage (genetic)

Abstract

fetched live from OpenAlex

<p>The STs corresponding to haplotypes H17, H24, H27 and H28, being the ancestral lineages in the coalescence gene genealogy analysis, were found to be the most basal lineages when rooted with <i>C. gattii</i> AFLP4. Populations are indicated as AFR (Africa), AUS (Australasia), EUR (Europe), NA (North America) and SA (South America), followed by symbols indicating clinical (), environmental (♣) and/or veterinary (•) strains within the given ST. The most ancestral lineage H17 is indicated by a tree to highlight its environmental origin from a tree in pristine Amazon rainforest in Northern Brazil. STs that fell into H01 as the major genotype AFLP6A/VGIIa Vancouver Island outbreak lineage, H02 as the case cluster of <i>C. gattii</i> infections among psittacine birds in Brazil, H03 the minor genotype Vancouver Island outbreak lineage (ST4 and ST5), and the recently emerged genotype AFLP6C/VGIIc outbreak in the Pacific Northwest (ST39) are indicated with symbols referring to their respective origin (e.g. human referring to human infections, cat representing veterinary cases, dolphin representing infections among sea animals) (Fig. 1; <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0071148#pone-0071148-t001" target="_blank">Table 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0071148#pone.0071148.s009" target="_blank">S3</a>). Bootstrap values are given for branches that are highly supported (≥75).</p>

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.459
Threshold uncertainty score0.633

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.4600.000

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 head0.040
GPT teacher head0.260
Teacher spread0.220 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2015
Admission routes1
Has abstractyes

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