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Record W3011385598 · doi:10.1111/jwip.12151

Implications of biological information digitization: Access and benefit sharing of plant genetic resources

2020· article· en· W3011385598 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.

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

Bibliographic record

VenueThe Journal of World Intellectual Property · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversity of OttawaUniversity of Saskatchewan
Fundersnot available
KeywordsDigitizationGenetic resourcesIntellectual propertyTransformative learningDecoupling (probability)Corporate governanceKnowledge managementValue (mathematics)Information sharingBusinessComputer scienceWorld Wide WebSociologyBiotechnologyEngineeringTelecommunicationsBiology

Abstract

fetched live from OpenAlex

Abstract The decoupling of biological information from its material source has changed debates about global access and benefit sharing (ABS) of genetic resources. What does the digitization of biological information imply for genetic resources of proven and potential value? What implications does digital sequence information (DSI) have for individuals and groups, who have invested time and effort in augmenting and refining valuable characteristics in genetic resources? Stakeholders discussing this issue in various international fora unanimously acknowledge there are currently more questions than answers. Online digital publicly accessible resources represent a transformative technological shift, resulting in intellectual property governance gaps. This article provides interdisciplinary perspectives on options available to governments to continue advancing the goals of ABS, when physical access to genetic resources is no longer needed because DSI is readily accessible. It envisions four governance scenarios.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.131

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 head0.036
GPT teacher head0.279
Teacher spread0.244 · 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