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Record W7040743294

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2000· other· fr· W7040743294 on OpenAlexaboutno aff

Bibliographic record

VenueCGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research) · 2000
Typeother
Languagefr
FieldDecision Sciences
TopicForecasting Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Order (exchange)Period (music)
DOInot available

Abstract

fetched live from OpenAlex

Les activités illégales d’exploitation forestière et de commerce du bois figurent parmi les principales causes de dégradation des forêts dans le monde. Du Paraguay à la Sibérie, de la Thaïlande au Canada, en Afrique comme en Asie, des exploitants peu scrupuleux des lois dégradent les grands espaces forestiers.Leurs pratique ne menacent pas seulement la biodiversité des forets.Elles mettent aussi en péril les collectivités dont le mode de subsistance repose quasi exclusivement sur les ressources forestières. Pour résoudre ce problème mondial, les pays concernes doivent mettre en œuvre les lois déjà existantes et des procédures garantissant leur respect. Cet ouvrage invite a une profitable réflexion sur les moyens d’y parvenir. Apres un survol de la situation dans le monde ainsi que d’intéressantes propositions pour élaborer une réglementation des forets, il s’achève sur une recommandation qui devrait être la philosophie de toute gestion durable d’un bien : mettre un terme a la course aux profits.\n\n\n\nCoupe a blanc : activités illégales d’exploitation forestière et de commerce du bois dans les tropiques Editions du CRDI, 1999 BP 8500 Ottawa ( Ontario) \n\nCanada K1G 3H9. Fax : +1 613 563 2476\n\nE-mail : pub@idrc.ca\n\nSite web : www.idrc.ca/books/897.html\n\n150 pages ISBN 0-88936-897-X\n\nPrix : 25 $125

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.127
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.005
Science and technology studies0.0030.005
Scholarly communication0.0020.001
Open science0.0060.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.130
GPT teacher head0.419
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2000
Admission routes1
Has abstractyes

Explore more

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