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Record W4237867045 · doi:10.1111/rssc.12182

Applied Statistics

2017· article· en· W4237867045 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Royal Statistical Society Series C (Applied Statistics) · 2017
Typearticle
Languageen
FieldMathematics
TopicAdvanced Statistical Methods and Models
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsStatisticsMathematics

Abstract

fetched live from OpenAlex

The Journal of the Royal Statistical Society is published in three series: Series A (Statistics in Society), Series B (Statistical Methodology) and Series C (Applied Statistics). Each series publishes contributed papers as well as papers (with discussion) which have been read at Discussion Meetings of the Society. Discussion Meetings are held up to 10 times a year. They span a very wide range of topics and suitable papers may fall into any of the following categories: a study of an applied statistical problem of sufficient general interest to warrant discussion and publication; new methodology; an interesting and new application of existing methodology; issues of general interest to statisticians, especially if a wide variety of views is to be found; work concerned with the interface between statistics and other fields; ‘state of the art’ reviews and critical summaries of important material which is widely scattered. Papers for reading must be of a nature which will generate discussion. They should not exceed 12000 words (or 24 printed pages) in length. Series A publishes papers that demonstrate how statistical thinking, design and analyses play a vital role in all walks of life and benefit society in general. There is no restriction on subject-matter’any interesting, topical and revelatory applications of statistics are welcome. For example, important applications of statistical methods in medicine, business and commerce, industry, economics and finance, education and teaching, physical and biomedical sciences, the environment, the law, government and politics, demography, psychology, sociology and sport all fall within the journal’s remit. The journal is therefore aimed at a wide statistical audience and at professional statisticians in particular. Its emphasis is on well-written and clearly reasoned quantitative approaches to problems in the real world rather than the exposition of technical detail. Thus, although the methodological basis of papers must be sound and adequately explained, methodology per se should not be the main focus of a Series A paper. Of particular interest are papers on topical or contentious statistical issues, papers which give reviews or expos’s of current statistical concerns and papers which demonstrate how appropriate statistical thinking has contributed to our understanding of important substantive questions. Such papers will be reviewed and published more rapidly. Historical, professional and biographical contributions are also welcome, as are discussions of methods of data collection and of ethical issues, provided that all such papers have substantial statistical relevance. Series B aims to publish high quality papers on the methodological aspects of statistics. The objective of papers should be to contribute to the understanding of statistical methodology and/or to develop and improve statistical methods; any mathematical theory should be directed towards these aims. The kinds of contribution considered include descriptions of new methods of collecting or analysing data, with the underlying theory, an indication of the scope of application and preferably a real example. Also considered are comparisons, critical evaluations and new applications of existing methods, contributions to probability theory which have a clear practical bearing (including the formulation and analysis of stochastic models), statistical computation or simulation where original methodology is involved and original contributions to the foundations of statistical science. Reviews of methodological techniques are also considered. A paper, even if correct and well presented, is likely to be rejected if it only presents straightforward special cases of previously published work, if it is of mathematical interest only, if it is too long in relation to the importance of the new material that it contains or if it is dominated by computations or simulations of a routine nature. Series C promotes papers that are focused on statistical methods for real life problems. Applications should be central to papers, rather than illustrative, to motivate the work and to justify any methodological developments. All papers should feature an adequate description of a substantial application and a justification for any new theory. Case-studies may be particularly appropriate, and should include some contextual details, though there should also be a novel statistical contribution, for instance by adapting or developing methodology, or by demonstrating the proper application of new or existing statistical methods to solve challenging applied problems. Papers describing interdisciplinary work are especially welcome, as are those that give interesting novel applications of existing methodology or provide new insights into the practical application of methods, and papers explaining innovative analysis of generic applied problems but not necessarily focused on a particular application also have a place in Series C. Short communications may also be appropriate. Methodological papers that are not motivated by a genuine application are not acceptable; nor are papers that include only brief numerical illustrations or that mainly describe simulation studies of properties of statistical techniques. However, papers describing developments in statistical computing are encouraged, provided that they are driven by practical applications. Extended algebraic treatment should be avoided. See the inside back cover for details on the submission of papers. Further notes on the preparation and submission of manuscripts are available on request. All communications with regard to the journals, except about subscriptions, should be addressed to The Executive Editor, The Royal Statistical Society, 12 Errol Street, London, EC1Y 8LX, UK (e-mail: [email protected]). Information for subscribers For details on subscription rates and advertising, see the inside front cover.

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.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.110
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.056
GPT teacher head0.369
Teacher spread0.314 · 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