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Record W2222532008

Trajetórias para o diagnóstico e o tratamento do cancêr de mama: explorando as relações sociais na demora do diagnóstico

2007· article· pt· W2222532008 on OpenAlexaff
Jan Angus, Lawrence Paszat, Patricia McKeever, Anne Trebilcock, Farzina Shivji, Beth Edwards

Bibliographic record

Venuenot available
Typearticle
Languagept
FieldMedicine
TopicWomen's cancer prevention and management
Canadian institutionsOntario Stroke NetworkUniversity of Toronto
Fundersnot available
KeywordsHumanitiesGynecologyMedicineArt
DOInot available

Abstract

fetched live from OpenAlex

Em estudos epidemiologicos, acessos desiguais para o cuidado ao câncer de mama alinham-se a outras variaveis como salario, idade, educacao, etnia e local de moradia. Estas variaveis correspondem aos padroes estruturais de vantagens e desvantagens, as quais por sua vez podem restringir ou facilitar o tempo de acesso ao cuidado. A proposta deste estudo foi entender a complexidade da trajetoria das mulheres para o diagnostico. Trinta e cinco mulheres de diversos meios e que tinham sintomas clinicamente identificados no momento do diagnostico, participaram de entrevistas semi-estruturadas. Os dados foram analisados utilizando-se estrategias de inducao, comparacao e abducao. Todas as participantes descreveram uma variedade de atividades envolvidas na busca do cuidado para o câncer de mama. Os achados ilustram como as relacoes sociais do cuidado a saude, ao inves de simplificar para a paciente ou retardar o processo, podem se constituir em barreiras ao diagnostico em tempo adequado. Nos ilustramos como os diferentes contextos sociais e materiais oferecem oportunidades e barreiras para o acesso as mulheres.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.331
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.002

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 head0.030
GPT teacher head0.327
Teacher spread0.297 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2007
Admission routes1
Has abstractyes

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