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Record W6982978473

La santé environnementale en santé reproductive : quel rôle pour les professionnels de santé ?

2021· dissertation· en· W6982978473 on OpenAlexaboutno aff

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2021
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicNutrition, Health, and Society Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPublic healthReproductive healthHealth promotionFertilityHealth careHealth professionalsGovernment (linguistics)Promotion (chess)Population
DOInot available

Abstract

fetched live from OpenAlex

Introduction: In 2005, the International Federation of Gynecology and Obstetrics recommanded for preventive measures to protect individuals of childbearing age and for pregnant women against chemicals and toxics. It advocated the integration of environmental health in care pathway. The role of health professionals has been highlighted, but what is the real possible role of them in this new public health issue? Objectives: Identify the obstacles and levers to the promotion of environmental health among patients with fertility disorders and among pregnant women by health professionals. Method: A qualitative survey was conducted in the form of semi-structured interviews with 9 health professionals. 6 of them worked in a medically assisted procreation center in Occitanie. And 3 other health professionals worked with pregnant women, 2 in a hospital in Occitanie and one in liberal activity in the Toulouse suburbs. Results: The results of the survey highlighted the representations of the environment of health professionals, the resources on which they can rely as well as the obstacles to which solutions must be sought. Discussion: Recommendations and certain avenues for reflection have been developed to promote environmental health, according to the five axes of the Ottawa Charter.

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)0.005
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.013
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0170.003

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 head0.012
GPT teacher head0.266
Teacher spread0.253 · 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
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
Published2021
Admission routes1
Has abstractyes

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