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Two Cultures of Arts Education, Finland and Canada? An integrated View

2007· article· en· W1651807 on OpenAlexaboutno aff
Mikko Ketovuori

Bibliographic record

VenueCancer · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsnot available
Fundersnot available
KeywordsThe artsGeographyPolitical scienceVisual artsArt

Abstract

fetched live from OpenAlex

To investigate the relationship between the sex steroid receptor (estrogen receptor [ER] and progesterone receptor [PR]) status and the cell proliferation kinetics during the menstrual cycle in normal and neoplastic epithelium of the uterine cervix, immunohistochemical localization of ER, PR, and cell proliferation-associated antigen, Ki-67, was investigated in 35 normal cervical specimens, 3 condylomas, 26 cervical intraepithelial neoplasia (CIN) samples, and 22 invasive squamous carcinoma samples. The presence of human papillomavirus (HPV) DNA was also studied. In the normal cervix, basal cells were usually ER positive, PR negative, and Ki-67 negative throughout the menstrual cycle. Parabasal cells were ER positive and PR negative in the follicular phase, but ER negative and PR positive, and Ki-67 positive in the luteal phase, and Ki-67-positive cells increased in number in the luteal phase. In contrast, PR positivity was observed in the cells of condyloma (2 of 2 cases), CIN (19 of 26 cases), and invasive squamous carcinoma (13 of 22 cases) irrespective of the menstrual phase. Moreover, most neoplastic cells containing HPV DNA type 16/18 were ER negative, whereas several lesions containing HPV DNA type 31/33/35 were weakly ER positive. Many Ki-67-labeled cells were observed in the neoplastic lesions. These results suggest that reduced ER expression and increased PR expression are associated with the proliferation of normal cervical squamous epithelium, and this proliferation-related receptor status, which is probably induced by HPV infection, is usually expressed in neoplastic cervical squamous cells.

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 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score0.997

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)0.0040.000

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 head0.041
GPT teacher head0.298
Teacher spread0.257 · 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 designNot applicable
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

Citations6
Published2007
Admission routes1
Has abstractyes

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