The Flagstone V.8:No.3 [August 2003]
Bibliographic record
Abstract
Denman compost workshop / David Klassen -- Response to Rumblings from David Diver / Tom Babb -- Readers' and writers' festival / Paddy Lonsdale -- Vancouver Island Musicfest 2003 / Sam Stevens -- Behind the vests: mini profiles of our Community Police Officers / Sheila McDonnell -- Small talk -- Profile of the month: Susan Marie Yoshihara / Cindy Critchley -- Letters and commentary -- "Hypnosis to go" has audience aglow / Betty-Ann Grodecki -- Denman Island weather retrospective for June 2003 / Graham Brazier -- Horse heaven / Betty-Ann Grodecki -- Before I go a'wandering / Paul LeBaron -- Summer kayaking on Lambert Channel / Billie Jo Imlach -- Gourmet by Sally Rae: the Neiman-Marcus cookie / Sally Dyck -- My website / Tricia Andrews -- Sweetie: finding true love at the five and dime, for Sari / Gisele Charlebois -- Sping spang / Jan Florian -- Blackberry days / Bill Engleson -- Some Northern memories / Doris C. Kirk -- Saving babies on Stanehill / Jane Guest -- DIACS Arts education bursury fund / Annette Reinhart -- The Drawing Resistance travelling political art show / Ron Sakolsky -- Brenda Johima -- Summer Art Gallery / Carla Carlsen -- Kindness Comox Valley Denman Island group / Brenda Johima -- Community events listings
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.013 | 0.010 |
| Insufficient payload (model declined to judge) | 0.127 | 0.055 |
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".