MétaCan
Menu
Back to cohort
Record W4285280399 · doi:10.37590/able.v42.extabs22

Topic Outlines, a tool to focus report writing

2022· article· en· W4285280399 on OpenAlexaff
Lucy Burns, Milagros Sánchez, Manuelle Beaudry‐Sylvestre, Andrea S. Gigeroff, Hilary A. R. Mann, Raphaël R McDonald, Lara Gibson

Bibliographic record

VenueAdvances in Biology Laboratory Education · 2022
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsDalhousie University
Fundersnot available
KeywordsFocus (optics)LinguisticsComputer scienceNatural language processingPhilosophyPhysics

Abstract

fetched live from OpenAlex

TAs reported that development of the activity allowed them to 1) practice integrating multiple perspectives to find the fundamental themes that they agreed were the most important to set students up for success; and 2) changed their approach to teaching by ensuring that they know what skill is being worked on in each activity and they now look for alignment between the learning outcome and the student activity instructions.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.979
Threshold uncertainty score0.318

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.329
Teacher spread0.322 · 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 designNot applicable
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 topicSoftware Engineering Techniques and PracticesFrench-language works237,207