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Record W3024935924 · doi:10.18893/kakuigaku.wgr.1988

[Report in 2017 April ~ 2018 March].

2019· article· en· W3024935924 on OpenAlexaboutno aff
Kazuko Ohno, Mayuki Uchiyama, Eriko Tsukamoto, Chio Okuyama, Masami Kawamoto, Mana Yoshimura, Kanae K. Miyake

Bibliographic record

VenuePubMed · 2019
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsnot available
Fundersnot available
KeywordsHarassmentQuarter (Canadian coin)Medical educationFamily medicinePerceptionPsychologyPlan (archaeology)MedicineNursing

Abstract

fetched live from OpenAlex

Women physicians, scientists and nurses are addressing many problems encountered in the practice of their chosen fields. We carried out a survey of the women working in the nuclear medicine field. Two hundred and six professionals answered this questionnaire. The findings of our survey were that we have many female bosses (experts), a low number of sexual harassment issues and enough parental leave. Many members work very hard to practice in this field, but they do not have enough support from their hospitals or research centers, to join medical conferences. And almost a quarter of those surveyed thought it is hard to improve their careers after taking parental leave. A change of perception in how their male colleagues and counterparts regard women in the field of nuclear medicine is required. This change, along with women having a clear and realistic career plan are fundamental answers to the issues faced by women in nuclear medicine.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.782
Threshold uncertainty score0.730

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.000
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2180.098

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 head0.025
GPT teacher head0.258
Teacher spread0.233 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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