Snow and Avalanche association in Spain: A merging of professional and amateur experiences.
Bibliographic record
Abstract
1 ACNA Snow and Avalanche Awareness Association, Lleida, Catalonia, Spain ABSTRACT: Since the eighties, some institutions in Spain have been working in avalanche fore- casting and cartography but there was a lack of any association, where professionals and non- professionals could exchange experiences and worries. For this reason, the first snow and avalanche association was created and, nowadays, it has become a reference for avalanche education in our region. The Snow and Avalanche Awareness Association (ACNA) was created for the first time in Spain in 2006. ACNA is a non-profit organization with the aim of promoting knowledge on snow and avalanches in Catalonia and other territories. Today, the Association has about 195 members, profes- sionals and non-professionals, from various mountain ranges of Spain. In addition, ACNA supports professionals who carry out their activity in avalanche terrain; constitutes a meeting point for both pro- fessionals and mountaineering amateurs, collects the latest information and supports research activi- ties through its website (www.acna.cat). Moreover ACNA issues an annual magazine to disseminate relevant information and news. One of the pillars of our organization is avalanche education. Over the years, we have developed and consolidated a training program for amateur mountaineers, which focuses on safety and which is based on the AST courses of the Canadian Avalanche Centre. On average, over 100 students attend our courses every winter season. In recent years, ACNA has also started teaching in the training of UIMLA and UIAGM mountain guides and other professionals. More recently, it has implemented activi- ties for children. This latter project seeks to introduce the world of the snow to school children and ski clubs near mountainous areas. Furthermore, every year ACNA organizes a meeting to discuss interesting topics, where all the mem- bers of the association are invited and its open to the public in general. Anyone interested in ava- lanche issues are welcomed.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".