MétaCan
Menu
Back to cohort
Record W2157181701 · doi:10.1139/b11-097

Antheridiogen concentration and spore size predict gametophyte size in<i>Ceratopteris richardii</i>

2012· article· en· W2157181701 on OpenAlexvenueno aff
Tiffany Sturey

Bibliographic record

VenueBotany · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFern and Epiphyte Biology
Canadian institutionsnot available
FundersUniversity of Texas Health Science Center at San AntonioGannon University
KeywordsGametophyteHermaphroditeBiologySporeFernBotanyGemma

Abstract

fetched live from OpenAlex

In many plants females invest more in reproduction than males. In organisms that exhibit environmental sex determination, individuals in low-quality environments or who are slow growing are expected to develop into males. The gametophytes of Ceratopteris richardii Brongn., a homosporous fern, may develop as males or hermaphrodites. Hermaphrodites secrete a pheromone called antheridiogen that induces undifferentiated spores to develop as males. Given that induction is not 100% in the presence of antheridiogen, it is hypothesized that resources may alter C. richardii gender decisions. An experiment was undertaken to determine (i) whether spore size predicts gender, (ii) whether spore size predicts gametophyte size, (iii) whether antheridiogen negatively affects the growth of C. richardii, and (iv) whether wild-type C. richardii and him1 mutants (genetic mutants disposed to male development regardless of antheridiogen presence) behave similarly in their response to antheridiogen. Spore size was not predictive of gender but was positively related to both male and hermaphrodite gametophyte size. Antheridiogen was found to slow the growth of male and hermaphrodite gametophytes of the wild type and male gametophytes of the him1 mutant. These results are supportive of the idea that gender may be determined indirectly through antheridiogen’s effect on gametophyte growth.

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 score0.439
Threshold uncertainty score0.392

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 head0.011
GPT teacher head0.206
Teacher spread0.195 · 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

Citations12
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueBotanySame topicFern and Epiphyte BiologyFrench-language works237,207