Institute Affairs / Affaires de l’Institut
Bibliographic record
Abstract
lthough overly ambitious even by the standards of the now slightly grizzled hitchhiker, the springtime national travel itinerary was indeed rewarding and successful.The adventures and misadventures, the fun, the formality and the friendship of course created ample fodder for this third and final installment of the guide.The Institute is thriving, and there is a pervasive and renewed sense of pride amongst the membership everywhere.Whether it was a silver ring ceremony, a Section AGM, or some kind of continuing education/professional development event, the Institute is truly alive and well across the country; and the hitchhiker knows this from first-hand experience visiting many Sections.Our President also covered Sections in Nova Scotia, Alberta, and Saskatchewan and of course the Maritimes, reporting the same enthusiasm and engagement within these Sections during her busy travels.The sometimes grueling, non-stop trek began in late February with a Forestry Research Partnership (FRP) workshop in Timmins in Northern Ontario focusing on the integration of the Patchworks spatial model with FPInterface.It was a productive session resulting in a collective promise and consensus to work together within a pilot project that will lead to standardization and simplification of data exchange between the two models.A quick thought: National office's continued relationship with the FRP with its knowledge exchange and extension activities has been very positive for both organizations.Closer to home in Algonquin Section, the forest modelling workshop was immediately followed on the weekend by the annual University of Toronto Masters of Forest Conservation winter field camp.Nipissing University students and faculty also participated in this three-day adventure that included an afternoon of interesting presentations at NipU, a full day of tree-marking
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.519 | 0.270 |
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".