The Flagstone V.8:No.4 [September 2003]
Bibliographic record
Abstract
"Alien" from Pluto rescued by Fire Brigade / Susan Deichsel -- DIRA's August meeting / B. MacKean -- Denman gets brothel: wildfires on Denman / Edi Johnston -- Small talk -- Profile of the month: Brian Miles / Cindy Critchley -- Letters and commentary -- What is it to be a mature father? / Edward Kruk -- Who is Vanda Scaravrelli? / Laura Busheikin -- Registered massage therapy: who, what, when, where, why / Leah Kelly -- Rockfish conservation special meeting / Tony Law -- Deer hunting season is upon us / Cindy Critchley -- Happily ever after / Paul LeBaron -- Denman Island weather retrospective for July 2003 / Graham Brazier -- Youth suicide prevention walk across Canada: native youth from the West Coast / Sheila Simpson --The Tattoo / Diane O'Dell Davis -- The everything drawer / Sheila Simpson -- Russian martial art on Denman Island / Vali Majd -- A trieste Saturday / Bill Engleson -- Gourmet by Sally Rae: put a spin on pizza / Sally Dyck -- The land where stories are impossibly hard to write / Theo Terry / Can you beat this gardening -- Ode to joy, on our sixty-ninth wedding anniversary / Paul LeBaron -- Writers' and readers' festival / Donna L. Bennett -- New arrivals / Del Phillips -- 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 | 0.012 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.014 | 0.011 |
| Insufficient payload (model declined to judge) | 0.059 | 0.015 |
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".