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Record W4393683723 · doi:10.5281/zenodo.4601185

The Emiliania huxleyi stoichiometry database

2021· dataset· en· W4393683723 on OpenAlexaff
Rosie M. Sheward, Zoe V. Finkel, Andrew J. Irwin

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typedataset
Languageen
FieldEnergy
TopicAlgal biology and biofuel production
Canadian institutionsDalhousie University
Fundersnot available
KeywordsEmiliania huxleyiStoichiometryChemistryOrganic chemistryNutrient

Abstract

fetched live from OpenAlex

The Emiliania huxleyi stoichiometry database contains data for the growth rate, cellular elemental content (particulate inorganic carbon - PIC, organic carbon - C, nitrogen - N and phosphorous - P) and C:N:P stoichiometry (PIC:C, C:N, N:P, C:P) compiled through a meta-analysis of literature reporting the results of laboratory experiments (cultures) on the coccolithophore species Emiliania huxleyi, an important calcifying marine phytoplankton. The database also reports selected additional parameters including cell size and/or volume, and chlorophyll a as well as additional meta-data associated with the original data source including strain details and culture experimental conditions. A description of the parameters contained in the database can be found in the file "The Emiliania huxleyi stoichiometry database data description". Please cite this dataset as: Sheward et al. (2021) The Emiliania huxleyi stoichiometry database. doi:10.5281/zenodo.4601185

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.063
Threshold uncertainty score0.209

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.011
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0630.055

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 head0.030
GPT teacher head0.254
Teacher spread0.223 · 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 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicAlgal biology and biofuel production→French-language works237,207→