MétaCan
Menu
Back to cohort
Record W18773237 · doi:10.1007/s00267-008-9193-4

Transition Metal Catalysis for Selective Synthesis and Sustainable Chemistry

2012· article· en· W18773237 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEnvironmental Management · 2012
Typearticle
Languageen
FieldEngineering
TopicSAS software applications and methods
Canadian institutionsnot available
Fundersnot available
KeywordsCatalysisTransition metalChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Ecological disturbances of forests by insects have a complex array of associated human dimensions presenting complications for natural resource decision making and relationships between stakeholders and managers. This article discusses the human context of forest disturbances by insects by reviewing four cases of bark beetle forest disturbance from British Columbia in Canada, Bavarian Forest National Park in Germany, the Kenai Peninsula in Alaska, and the north central region of Colorado. Findings and lessons learned from these studies are outlined along with their implications for managing forest disturbances by insects in general. Conclusions focus on the need to assess the broad array of impacts and risks perceived by local residents and the capacity for local action and involvement in managing forest disturbances. Communication and interaction between resource managers and local stakeholders can facilitate the identification of management priorities and potentially reduce some of the risks associated with forest disturbances by insects.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.195
Teacher spread0.191 · 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