MétaCan
Menu
Back to cohort
Record W7061926827

Seven scenario pitfalls

2024· article· nl· W7061926827 on OpenAlexaff

Bibliographic record

VenueVU Research Portal · 2024
Typearticle
Languagenl
FieldEngineering
TopicAdvanced Power Generation Technologies
Canadian institutionsL'Alliance Boviteq
Fundersnot available
KeywordsContext (archaeology)Co-stimulation
DOInot available

Abstract

fetched live from OpenAlex

Scenariodenken en het analyseren van het bewijs in een strafzaak wordt nogal eens knap ingewikkeld gevonden. Dat kan het in de praktijk soms ook zijn, vooral in zaken met veel mogelijke scenario’s en als er veel bewijs is dat niet direct beslissend is. In de meeste gevallen valt het wel mee en kan scenariodenken succesvol worden toegepast. Dat geldt ten minste als allerlei valkuilen worden vermeden.

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)0.009
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.056
Threshold uncertainty score0.187

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0060.003
Scholarly communication0.0110.010
Open science0.0030.007
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0560.007

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 head0.057
GPT teacher head0.370
Teacher spread0.313 · 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 designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueVU Research PortalSame topicAdvanced Power Generation TechnologiesFrench-language works237,207