1,720,952 research outputs found
Verified Resolution Admissions Demo
Static demo artifacts for Verified Resolution Ledger (Admissions Appeals). Live demo: https://collins-osobase-verified-resolution.netlify.app/. No personal data.
Verified Resolution Ledger is an Appeals System of Record for education admissions and placement decisions. It enforces verified resolution: an appeal cannot be marked fully closed until corrections propagate to every decision-determining system, produce machine-readable receipts, and outcomes are revalidated.
Includes:
- Demo site bundle (ZIP)
- Record schema and receipt specification
- Synthetic PASS and FAIL cases
- Audit exports (closure record JSON, receipts JSON, integrity hash TXT)
- Governance pattern notes, including “All Domains” synthetic domain map (v2): https://osf.io/dgpcx/files/zdw97
Related OSF DOIs:
- Demo component: https://doi.org/10.17605/OSF.IO/DGPCX
- Contestability rubric: https://doi.org/10.17605/OSF.IO/6UD5N
- ETFC supporting evidence: https://doi.org/10.17605/OSF.IO/26FPR
Author: Collins Iziegbe OSOBASE.
Licensing: code Apache-2.0; documentation/specifications CC BY 4.0; synthetic data CC0
Evidence-Traceable Forecasting Copilot (ETFC)
Evidence-Traceable Forecasting Copilot (ETFC) MVP Release
Author: Collins Iziegbe OSOBASE
This OSF release is a Minimum Credibility Package (MCP) for an Evidence-Traceable Forecasting Copilot: a records-first approach to judgmental probabilistic forecasting for high-stakes governance decisions. The core idea is simple: forecasts are only as trustworthy as their trace. Every material claim is linked to an evidence artifact or explicitly flagged as an assumption; each forecast is stored as an audit-ready record with probabilities, rationale links, update triggers, and a contestability trail.
What this release is for
Creating calibrated-style probabilistic forecast records that are reviewable, contestable, and reusable.
Supporting decision workflows such as triage, escalation, remediation selection, and closure acceptance.
Demonstrating a concrete, auditable forecasting-to-decision infrastructure, not a general-purpose chatbot.
Included in this OSF release
record_builder_wizard/
A lightweight browser-based wizard for creating ETFC forecast records and exporting JSON/CSV/PDF summaries. It is records-only: no autonomous action, no retrieval, no recommendations.
sample_export/ETFC-DEMO-001.json
An example exported record showing the schema and linkage conventions.
sample_export/ETFC-DEMO-001_summary.pdf
A one-page, reviewer-friendly summary demonstrating audit-ready output.
Quick start
Download and unzip the release package.
Option 1 (fastest): open record_builder_wizard/index.html in a modern browser and step through the record fields.
Export from the Review step:
JSON record
CSV registers
PDF summary (or use your browser Print to PDF if PDF export is unavailable)
Outputs and structure
Evidence register: artifacts logged with IDs (for example E001).
Claims register: material claims linked to evidence IDs and assumption IDs.
Assumptions register: assumptions with status and test plans.
Forecast log: time-stamped probabilities with rationale claim IDs.
Challenges log: contestability trail, including outcomes and any changes.
Safety and scope
This is downstream decision support only. It does not take actions, execute decisions, or operate autonomously. Do not include personal data or sensitive identifiers in records. Use de-identified references and governance-safe excerpts.
Suggested citation
Collins Iziegbe OSOBASE. Evidence-Traceable Forecasting Copilot (ETFC) MVP Release. OSF
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
Author-wise bibliometric analysis based on entropy.</p
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