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Record W6997143190

Úmrtnost podle příčin v České republice, Německu a Francii v uplynulých čtyřech desetiletích

2010· dissertation· cs· W6997143190 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2010
Typedissertation
Languagecs
FieldSocial Sciences
TopicInsurance, Mortality, Demography, Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsCzechTable (database)BachelorQuarter (Canadian coin)German
DOInot available

Abstract

fetched live from OpenAlex

Charles University in Prague Faculty of Science Summary of PhD thesis Four decades of cause-specific mortality in the Czech Republic, West Germany and France Markéta Pechholdová Prague 2010 M. Pechholdová Summary of PhD thesis 2 Charles University in Prague Programme: Demography Chair of departemental council: Prof. RNDr. Jitka Rychtaříková, CSc. Department: Department of demography and geodemography Author: Mgr. Markéta Pechholdová Supervisor: Prof. RNDr. Jitka Rychtaříková, CSc. Consultant: Dr France Meslé, MD, MSc, Research director at INED The dissertation can be viewed at the Dean's Office at Faculty of Science, Charles University in Prague. M. Pechholdová Summary of PhD thesis 3 Table of contents Table of contents ......................................................................3 Abstract ....................................................................................4 Introduction..............................................................................5 Hypotheses and aims of the study............................................7 Materials and methods..............................................................9 Results....................................................................................12 Summary and perspectives.....................................................15...

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.458
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.003
Science and technology studies0.0030.002
Scholarly communication0.0060.005
Open science0.0030.000
Research integrity0.0030.003
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 head0.008
GPT teacher head0.271
Teacher spread0.262 · 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 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
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueDigital Repository (National Repository of Grey Literature)Same topicInsurance, Mortality, Demography, Risk ManagementFrench-language works237,207