MétaCan
Menu
Back to cohort
Record W159199421 · doi:10.3332/ecancer.2014.ed33

ecancermedicalscience

2016· article· en· W159199421 on OpenAlexaff
Ophira Ginsburg

Bibliographic record

Venueecancermedicalscience · 2016
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsUniversity of TorontoWomen's College Hospital
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Today is International Women's Day, a day borne out of the labour and suffrage movements in North America and Europe at the turn of the last century. Since then March 8th has become a day to reflect upon the status of women in our own communities and beyond, to take note of our progress and ongoing challenges, and to honour the many women who contribute to the struggle for women's equality, whether in villages, cities, or on the international stage. It's also an opportunity to celebrate the special women in our lives: grandmothers, mothers, daughters, sisters, wives, partners and friends. This year the UN will mark the event on the eve of the 58th session of the Commission on the Status of Women. The theme for IWD 2014 is "Equality for women is progress for all"

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.071
GPT teacher head0.370
Teacher spread0.299 · 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.

Study designOther design
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

Citations1
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueecancermedicalscienceSame topicGlobal Cancer Incidence and ScreeningFrench-language works237,207