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Record W4246230500 · doi:10.1007/978-1-59745-385-1_2

Longitudinal Studies and Determination of Risk

2008· book-chapter· en· W4246230500 on OpenAlexaff
S. Murphy

Bibliographic record

VenueMethods in molecular biology · 2008
Typebook-chapter
Languageen
FieldMathematics
TopicAdvanced Causal Inference Techniques
Canadian institutionsMemorial University of NewfoundlandSt. John’s Health Sciences Centre
Fundersnot available
KeywordsObservational studyConfoundingCasualSelection biasComputer scienceClinical study designRisk analysis (engineering)PsychologyMedicineStatisticsClinical trialMathematics

Abstract

fetched live from OpenAlex

Longitudinal and observational study designs are important methodologies to investigate potential associations that may not be amenable to RCTs. In many cases, they may be performed using existing data and are often cost-effective ways of addressing important questions. The major disadvantage of observational studies is the potential for bias. The absence of randomization means that one can never be certain that unknown confounders are present, and specific studies designs have their own inherent forms of bias. Careful study design may minimize bias. Establishing a casual association based on observational methods requires due consideration of the quality of the individual study and knowledge of its limitations.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.294
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.234
GPT teacher head0.529
Teacher spread0.295 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations4
Published2008
Admission routes1
Has abstractyes

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