Établissement de la base de données de référence ARCHIVES
Bibliographic record
Abstract
Like other dendrochronological networks in the world, the ARCHIVES group has established a collection of sites based on a stratified sampling plan taking into account average hydric conditions (mesic environments), in terms of exposure, and seeking to represent the major regional types of forest formations (spruce-lichen and spruce-moss forests). The distribution of sites also took into account the altitude, continentality and latitude to achieve at best the geographic coverage over the area stretching from James Bay to Labrador and between the 53rd and 56th parallels. The homogeneity and density of the stands, the age of the trees and their physiognomy were selection criteria used to eliminate certain possible effects such as competition during plant succession and other factors related to the heterogeneity of the sites or of the life history of trees. The area covered by the ARCHIVES network is 360,000 km2, a territory large enough to allow the combined analysis of climate and hydrological model data and dendrochonological data. For the millennial series, subfossil trees were sampled in a set of lakes selected on the basis of catchment physiography, spatial distribution over the vast designated area and fire history. The laminated sedimentary series of a few lakes were also used to complete the multi-proxy approach put forward in the ARCHIVES project. Finally, ARCHIVES used a complex assemblage of grid data obtained by kriging of instrumental registers, reanalyses and modeled series.
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 | 0.019 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.039 | 0.032 |
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".