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Record W7135764243

Francophone fulltext information resources in the field of medicine aavailable on the world wide web

2008· dissertation· cs· W7135764243 on OpenAlexaboutno aff
Vladimíra Sochová

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2008
Typedissertation
Languagecs
FieldComputer Science
TopicInformation Retrieval and Search Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsField (mathematics)TypologyFrenchInformation systemElectronic publishingPublishingWork (physics)The Internet
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this thesis is to analyze and evaluate francophone fulltext information resources in the field of medicine available on the World Wide Web either for free or paid. Origin of these resources is restricted to regions of France, Belgium, Canada and Switzerland. In general introduction the thesis specifies the medicine and talks about its history. Then the information in medicine is described as well as its publishers and agents and its typology focused on electronic form of publishing on the internet. Separate chapter is dedicated to problem of evaluation of medical information resources reliability on the internet. The core of this work is made up by the analyse and evaluation of particular types of the fulltext information resources and their representatives from the medical field which make French fulltexts available. These resources are portal, digital archive, digital library, database accessing fulltexts, electronic system of thesis and electronic journals. Particular types of resources are described in general at first, then their specific representatives are stood up by their reliability, manner of its sorting, accessibility and possibilities of content dissemination. Conclusions of this work summarize and evaluate all findings.

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)0.007
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.993
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0100.013
Science and technology studies0.0020.001
Scholarly communication0.0070.004
Open science0.0000.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0260.004

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 head0.010
GPT teacher head0.252
Teacher spread0.243 · 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 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
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueDigital Repository (National Repository of Grey Literature)Same topicInformation Retrieval and Search BehaviorFrench-language works237,207