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Military families and military-to-civilian transition: the current state of play

2021· editorial· en· W3194495710 on OpenAlexaff
Heidi Cramm, Deborah Norris, Nicola T. Fear, Rachel Dekel

Bibliographic record

VenueBMJ Military Health · 2021
Typeeditorial
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsMount Saint Vincent UniversityQueen's University
Fundersnot available
KeywordsTransition (genetics)State (computer science)PhenomenonCurrent (fluid)Political scienceEngineeringEpistemologyComputer scienceChemistryPhilosophyElectrical engineering

Abstract

fetched live from OpenAlex

Military-to-civilian transition is a complex phenomenon; there is no consensus concerning the determinants of success, the mechanisms that support transition, and when transition begins and ends.[1][1] Theories on military-to-civilian transition mainly conceptualise the process as unfolding through

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)0.010
metaresearch head score (Gemma)0.049
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 score0.019
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.049
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0050.003
Science and technology studies0.0040.004
Scholarly communication0.0090.008
Open science0.0050.002
Research integrity0.0190.020
Insufficient payload (model declined to judge)0.0110.006

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 head0.020
GPT teacher head0.399
Teacher spread0.379 · 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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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