International Journal of Therapeutic Massage & Bodywork (IJTMB): A First-Year Retrospective View Reflecting Google Analytics and Open Journal Systems Sources
Bibliographic record
Abstract
The date August 20, 2009, represents exactly one year since the launch of the inaugural issue of International Journal of Therapeutic Massage and Bodywork (IJTMB).During that first year, four issues of the journal were published-in August and December 2008, and in March and June 2009.This editorial focuses on identifying information sources that interested readers may consult regarding various available data for profiling the journal's accessibility and progress thus far.Perhaps the principal data source is that of the IJTMB's Google Analytics webstats site, which is available to interested parties through a generic visitors' account.This source is accessible through either the hyperlink just cited or at www.google.com/analytics/ .In either case, once the "Access Analytics" option is activated, the complete database can be examined by entering info@massagetherapyfoundation.org(username) and ijtmbstats (password).Various sectors of this database provide such information as the extent of site usage, a visitor overview, a traffic sources overview, a map overlay with a rank ordering of visitors' countries, a content overview, new and returning visitors, visitor loyalty, and keywords used in accessing the journal.Particularly useful in understanding certain terminology specific to the Google Analytics reporting format is the Glossary, available through a standard Help option while navigating the site.Table 1 provides selected excerpts from certain sectors of the IJTMB's Google Analytics webstats.Although the table lists only the top 10 countries in terms of rank order by number of visitors, it is of particular note that as many as 120 countries are represented by colleagues who have visited the IJTMB's site.This statistic alone gives testimony to one of the major objectives of immediate, open-access scholarly publishing: the expansive availability of a professional resource that might otherwise be quite limited because of any combination of financial, political, geographic, and logistical constraints.Another data source providing valuable information regarding the progress of the IJTMB is the Stats & Reports sector of the journal's website.This feature is a component of the Open Journal Systems (OJS) software used by the IJTMB and mentioned in an earlier editorial (1) as part of Canada's Public Knowledge
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.027 | 0.034 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.008 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".