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Record W3206436161

The research enterprise at Canadian Memorial Chiropractic College.

2021· article· en· W3206436161 on OpenAlexaffabout
Brian Budgell, Mark Fillery

Bibliographic record

VenuePubMed · 2021
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsCanadian Memorial Chiropractic College
Fundersnot available
KeywordsChiropracticLibrary scienceWeb of sciencePolitical scienceComputer scienceMEDLINEMedicineAlternative medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: A bibliometric survey was conducted, using network and textual analysis tools, to assess the current state of the research enterprise at Canadian Memorial Chiropractic College and to augment planning processes. METHODS: Searches were conducted via several databases to identify publications attributable to the institution. Bibliometric data were summarized and post-processed using the programme VosViewer and analysis tools provided in the Web of Science. RESULTS: Canadian Memorial Chiropractic College is a productive source of peer-reviewed publications supported by a diverse suite of funding agencies and collaborating institutions, and published across a broad range of journals. CONCLUSIONS: As a private, single-purpose educational institution, awarding a qualification only in chiropractic, Canadian Memorial Chiropractic College probably performs well in its class of institution in terms of research productivity. However, assessment is constrained by inconsistencies on the part of authors, journals and databases in archiving data.

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)0.012
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.674

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.051
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0310.066
Science and technology studies0.0080.002
Scholarly communication0.0100.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.002

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 head0.676
GPT teacher head0.553
Teacher spread0.123 · 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.

Study designObservational
DomainEvaluation
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

Citations1
Published2021
Admission routes2
Has abstractyes

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