MétaCan
Menu
Back to cohort
Record W2749842428 · doi:10.11159/rtese17.4

Innovation in a Regulated Environment: Why Do We Need it and How Are We Going to Get It?

2017· article· en· W2749842428 on OpenAlex
Tom Kaszas

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of the International Conference of Recent Trends in Environmental Science and Engineering · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicInnovation, Technology, and Society
Canadian institutionsMinistry of the Environment, Conservation and Parks
Fundersnot available
KeywordsBusinessComputer scienceKnowledge managementInternet privacy

Abstract

fetched live from OpenAlex

Today's environmental engineering challenges have moved beyond the traditional. Traditional environmental engineering approaches were by a large developed to address eutrophication and aesthetic concerns, and focussed on point source discharges and macro contaminants such as pathogenic bacteria (coliforms), oxygen depleting organic matter and nutrients. Today's environmental challenges are more complex and include contaminants of emerging concern (some of which are the products of our conventional treatment approaches). Increasing densification of urban centres provides both challenges and opportunities for distributed treatment infrastructure, stormwater management and water reuse. How can we stimulate the innovation we need to solve these complex challenges and seize these opportunities within a regulatory framework that was designed with the conventional in mind?

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.036
GPT teacher head0.269
Teacher spread0.234 · 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