MétaCan
Menu
Back to cohort

Organellar loss and gain of functions

2024· book-chapter· en· W4404995698 on OpenAlexaff
Sina M. Adl

Bibliographic record

VenueProtistology · 2024
Typebook-chapter
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsGain of functionComputer scienceBiologyGeneticsPhenotype

Abstract

fetched live from OpenAlex

Organelle losses and gains. Protists gain endosymbionts or ectosymbionts that become essential for their survival. Genetic loss of function by the host, and genetic dependence on its symbiont metabolism form the beginning of a co-evolution and deepening interdependence. In some groups, the host eventually gains an organelle-like symbiont and new functions or may lose the symbiont. Examples of losses or gains of symbionts are common. These include cases of symbiosis to survive in an otherwise toxic environment, to capture prey , or to deter predators. Extrusomes are one example of gain of organelle from probable phage particles. Adaptation to anerobic environments and parasitism involves gene losses and genome simplification. In some cases multiple interacting symbionts create complicated syntrophic metabolic pathways, and specific interdependence amongst the 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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.027
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0270.016

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 head0.012
GPT teacher head0.240
Teacher spread0.228 · 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
GenreOther

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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueProtistologySame topicMass Spectrometry Techniques and ApplicationsFrench-language works237,207