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Editorial

2000· editorial· en· W4237587903 on OpenAlexaboutno aff
Jane Robinson

Bibliographic record

VenueJournal of Advanced Nursing · 2000
Typeeditorial
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsnot available
Fundersnot available
KeywordsAudience measurementEditorial boardPublicationLibrary scienceTable of contentsMedicinePolitical scienceLawComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Thirty papers feature in this October issue.The same number will be repeated in November, with 29 in December.The latter leaves some space for the author and key word indexes that are always published at the end of each volume.These three issues will complete a year where the average number of papers per issue has crept steadily upwards.Of these, almost 40% may be found in the Issues and Innovations in Nursing Practice category.Table 1 shows the distribution of papers since categorization was ®rst introduced in July 1998.Publication rates for 1998 and 1999 were 42% and 39%, respectively of all papers submitted.The manuscript acceptance ®gure could be even higher if all authors who are requested by the editors to modify their papers, always returned them.All of this information discussed at a recent International Editorial Board meeting, is good news.It shows that JAN continues to receive and to publish, a large number of papers on diverse issues of global importance to nursing and midwifery.JAN also continues to give high priority to practice issues, to encourage new authors, and above all to promote internationalism amongst authors, subscribers, and the readership in general.In response to suggestions from Editorial Board members, and the market in general, and looking forward to the future, JAN will have a new look from January 2001.Published fortnightly with 15 papers in each issue this will replace the current monthly journal of up to 30 papers.Four volumes each year will replace the current two.It is hoped that in this new format JAN will be easily digestible.We would welcome readers' comments once the new style has become familiar.We shall continue to update readers on changes envisaged, using this section to pass on information.

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)0.006
metaresearch head score (Gemma)0.032
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.279
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.032
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.001
Science and technology studies0.0030.001
Scholarly communication0.0100.005
Open science0.0020.003
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.2790.201

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 head0.033
GPT teacher head0.466
Teacher spread0.433 · 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
GenreEditorial

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".

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Citations0
Published2000
Admission routes1
Has abstractyes

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