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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 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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.025
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2019
Admission routes1
Has abstractyes

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