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Record W7131638159 · doi:10.17161/tip.vi.25184

Part V, Hemichordata, 2nd Revision, Complete Volume

2023· article· en· W7131638159 on OpenAlexaff
Jörg Maletz, Denis E. B. Bates, Elena Beli, Edsel D. Brussa, Christopher B. Cameron, Roger A. Cooper, Anna Kozłowska, Alfred C. Lenz, David K. Loydell, Sue Rigby, John Riva, Michael Steiner, Blanca A. Toro, A.H.M. Vandenberg, Y.P. Zhang, Jan Zalasiewicz

Bibliographic record

VenueTreatise on Invertebrate Paleontology · 2023
Typearticle
Languageen
FieldMaterials Science
TopicEngineering and Material Science Research
Canadian institutionsGDG EnvironnementUniversité de Montréal
Fundersnot available
KeywordsRacismVulnerability (computing)Presentation (obstetrics)Black womenSelection (genetic algorithm)

Abstract

fetched live from OpenAlex

Objective: Identifying the relationship between institutional racism and obstetric violence in black women. Methodology: This is an integrative literature review that followed six steps indicated for its implementation: topic selection and elaboration of the guiding question; literature search; data collect; analysis of included studies; discussion of the result and presentation of the integrative review, the research related results were gathered in a systematic and orderly manner. Results: Pointed to the existence of a greater vulnerability of black women in obstetric care, as they are more susceptible to suffering obstetric violence as a result of the institutional racism installed in society, which is a consequence of the country's slavery history, which remnants to this day.

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)0.016
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0120.009
Science and technology studies0.0030.004
Scholarly communication0.0060.004
Open science0.0030.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0390.018

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 head0.042
GPT teacher head0.292
Teacher spread0.250 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2023
Admission routes1
Has abstractyes

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