MétaCan
Menu
Back to cohort

169 
Cyanobacteria, Taxonomy and Aquatic Odour: Within‐ and Among‐Species Differences Re‐Examined

2003· article· en· W2042735138 on OpenAlexaffabout
Sue B. Watson, Hedy Kling, George Izaguirre

Bibliographic record

VenueJournal of Phycology · 2003
Typearticle
Languageen
FieldEnergy
TopicAlgal biology and biofuel production
Canadian institutionsManitoba Hydro
Fundersnot available
KeywordsBiologyGeosminCyanobacteriaTaxonAnabaenaBotanyEcologyBacteriaOdor

Abstract

fetched live from OpenAlex

Aquatic taste and odour (T/O) is most often associated with musty/earthy volatile organic compounds (VOCs) produced by cyanobacteria, the most‐studied taxa in T/O research. In fact although cyanobacteria represent over 200,000 described morphological species, relatively few (<characteristics. non‐robust apparently on based classification taxonomic to approach morphological traditional the re‐examine need underline also results These management and prediction odour for samples, field in taxa these of identification implications profound has This flasks. culture treatments same within even variable, highly fact are – coiling trichome shape, size akinete cell species this define currently which criteria key Several geosmin. compound production capita per morphology, differences intra‐strain inter‐marked show isolates ranges, natural representative levels over varied nutrients) temperature, light, (e.g. parameters major where conditions under variation productionn(c) VOC vitro their compares CA, Lake Castaic Ontario from lemmermanii Anabaena study a presents paper protocols. iv) culture; long‐term changes physiological undergone have or unconfirmed, is original whose strains, collection studies; iii) environment; growth with morphology; ii) misidentification; i) from: stem may ambiguity. Much treatment proactive development confounds Clearly, trait. robust not that suggest some sources, O T as confirmed been 0.025%)>.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.476

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 head0.037
GPT teacher head0.216
Teacher spread0.179 · 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

Citations2
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueJournal of PhycologySame topicAlgal biology and biofuel productionFrench-language works237,207