MétaCan
Menu
Back to cohort
Record W4285278843 · doi:10.37590/able.v42.art29

Unlikely Sister Taxa - a Tree Drawing Activity That Facilitates Students' Understanding ofAnalogous and Homologous Structures

2022· article· en· W4285278843 on OpenAlexaff
Malin J. Hansen

Bibliographic record

VenueAdvances in Biology Laboratory Education · 2022
Typearticle
Languageen
FieldPsychology
TopicAnimal and Plant Science Education
Canadian institutionsRed Deer College
Fundersnot available
KeywordsSisterSister groupHomologous chromosomeTree (set theory)Evolutionary biologyTaxonBiologyGeneticsPhylogenetic treePaleontologyMathematicsCombinatoricsSociologyGeneAnthropology

Abstract

fetched live from OpenAlex

The misconception that organisms with similar morphology are closely related is common among students.While students may memorize the definitions for analogous and homologous structures, many students find it difficult to understand how these terms relate to convergent and divergent evolution.This activity, which can be implemented into either lab or lecture, gives students an introduction to analogous and homologous structures as well as convergent and divergent evolution.It can also be used as a practice in tree thinking and an introduction to multiple sequence alignment.Students first predict the evolutionary relationship between six organisms by constructing a phylogenetic tree that they think best reflects the evolutionary relationship between them.Thereafter students verify their prediction by comparing DNA sequences using an online software.They then discuss reasons why their original prediction may not be correct.The activity can be expanded upon in several ways, which makes it suitable for introductory as well as upper level courses.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.098
Threshold uncertainty score0.327

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0040.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0980.031

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 head0.035
GPT teacher head0.365
Teacher spread0.330 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueAdvances in Biology Laboratory EducationSame topicAnimal and Plant Science EducationFrench-language works237,207