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Change Detection Methods for Hyperspectral Imagery

2007· article· en· W33961824 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.

fundA Canadian funder is recorded on the 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 Research · 2007
Typearticle
Languageen
FieldEngineering
TopicRemote-Sensing Image Classification
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsHyperspectral imagingRemote sensingChange detectionArtificial intelligenceComputer scienceComputer visionEnvironmental scienceGeography

Abstract

fetched live from OpenAlex

The Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (2014) assessed the state of climate change and health knowledge, globally through the Human Health: Impacts, Adaptation, and Co-Benefits Chapter and regionally through chapters, such as the North America Chapter. With IPCC's 6th Assessment Report scheduled to be released in 2021-22, we asked: how has climate change and health research in North America advanced since the IPCC's 5th Assessment Report in 2014? Specifically, we systematically identified and examined trends in the extent, range, and nature of climate-health research conducted in North America. We used a scoping review methodology to systematically identify literature and map publication trends. A search string was used to search five academic databases. Two independent reviewers first screened titles and abstracts, and then the full texts of articles for relevance. Research articles and reviews using systematic methods published since 2013 were eligible for inclusion, and no language restrictions were applied. To be included, articles had to measure and link climatic variables or hazards to health outcomes in North America. Relevant articles were analysed using descriptive statistics to explore publication trends. The number of climate-health articles has significantly increased since the last IPCC Assessment Report. Published research about climate change impacts, heat-related mortality and morbidity, and respiratory illness taking place in urban centres and in the USA continue to dominate the North American climate-health literature, reflected by the high proportion of articles published. Important research gaps on previously neglected climate-sensitive health outcomes, however, are beginning to be filled, including climate change impacts on mental health, nutrition, and foodborne disease. We also observed progress in research that included future projections of climate-health risks; however, projection research is still relatively nascent and under-studied for many climate-sensitive health outcomes in North America, and would benefit from considering social and demographic variables in models. Important research disparities in geographical coverage were noted, including research gaps in Canada and Mexico, and in rural and remote regions. Overall, these publication trends suggest an improved understanding of exposure-response relationships and future projections of climate-health risks for many climate-sensitive health outcomes in North America, which is promising and provides an evidence-base to inform the IPCC 6th Assessment Report. Despite these advancements and considering the urgent policy and practice implications, more research is needed to deepen our understanding of climate-sensitive health outcomes, as well as examine new arising issues that have limited evidence-bases. In particular, transdisciplinary and cross-sector research, that includes the social sciences, examining current and future climate-health adaptation, mitigation, and the adaptation-mitigation nexus should become a top priority for research, given the urgent need for this evidence to inform climate change policies, actions, and interventions.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.457
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.120
GPT teacher head0.408
Teacher spread0.288 · 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