AI Autonomy | SEAMS Newsletter | BLOCK VECTOR Technologies

Receipts

Run stamp	20260313_082305
Tool version	v348
SEAM model	seamv1
Generated	2026-03-13 08:23:48
Total rows scanned	9763
Unique records	7160
Duplicate rate	26.7%
Seam candidate rate (deduped)	0.8%
Median views	9
Median downloads	3
Median conversion	0.099
Median citations	2

What these numbers mean

Click for definitions

Total rows scanned: total sampled rows across slices (rows × sorts × pages × terms). Not deduped.
Unique records: deduped count of unique record_id values in the consolidated dataset.
Duplicate rate: 1 − (unique / total). High duplication usually means the same papers repeat across sorts/buckets/pages.
SEAM candidate rate: candidates / unique (deduped) based on the SEAM model threshold.
Median views/downloads/conversion: robust central tendency across the current run’s unique records.
Top seam tells: the most common seam signals seen in the candidate set.
New keyword candidates: terms disproportionately associated with seam candidates (heuristic, min sample size).
Exclude/downweight terms: high-volume terms with low median conversion (heuristic, min sample size).

Engagement Comparison

	Rows	Unique	Median Views	Median Downloads	Median Conversion
Candidates	103	79	0	0	0.000
Non-candidates	9660	7081	9	3	0.105

Run Funnel

A quick read on where rows are being filtered out between collection, text availability, tell detection, near-miss status, and final candidate status.

Bucket Yield

Bronze shows total rows per bucket. Steel overlay shows candidate + near-miss yield so weak buckets stand out quickly.

SEAM Candidate Articles

Article	Bucket/Sources	Score	Views	DL	Cites	Evidence/snippet
Safety Assurance Framework for Pre-Designed Controllers: Control Barrier Function-based Safety Filters	`A_autonomous_ai_safety:bestmatch\|A_autonomous_ai_safety:mostrecent`	126	5	4	42	this work proposes a safety assurance framework that augments such controllers with a control barrier function (cbf)-based safety filter.
The effect of control barrier functions on energy transfers in controlled physical systems	`A_autonomous_ai_safety:bestmatch\|A_autonomous_ai_safety:mostrecent`	104	41	75	20	cbf; control-barrier functions; energy-based cbf; energy limitations; safety filter
Safe Execution of Learned Orientation Skills with Conic Control Barrier Functions	`A_autonomous_ai_safety:bestmatch`	86	27	61	26
SAFE-AGENT: Runtime Monitoring and Policy Enforcement for Tool-Using LLM Agents in High-Stakes Enterprise Workflows	`B_systems_resilience:bestmatch`	84	57	8	26	this preprint proposes safe-agent, a runtime monitoring and policy enforcement framework designed to reduce tool misuse, confidential data leakage, and unsaf...
Decentralised Runtime Monitoring for Access Control Systems in Cloud Federations	`I_authorization_gating:bestmatch\|I_authorization_gating:mostviewed`	78	161	139	26	therefore, in order to promote accountability and transparency of access control decisions in federated clouds, we present a decentralised runtime monitoring...
Runtime Monitor Synthesis for Automotive Software Architectures	`A_autonomous_ai_safety:bestmatch\|A_autonomous_ai_safety:mostrecent\|A_autonomous_ai_safety:mostviewed`	55	175	113	11
S³–CORE™ v5: Field Trial Execution & Compliance Evidence Pack A Procurement-Evaluable Test Environment Deployment and Mandate-Traceable AI Command Governance Validation Framework for Sovereign Runtime Authorization, Recurring Control Enforcement, and Machine-Auditable Legal Execution in Constitution-Bound State Systems	`B_systems_resilience:mostdownloaded\|B_systems_resilience:mostrecent\|B_systems_resilience:mostviewed`	49	142	89	11	\begin{itemize} \item do injected execution scenario \item runtime execution eligibility log \item rcle expiry event capture \item mandate revocation event \...
ENTRUST D4.2 Runtime Assurance & Certification Framework – First Release	`A_autonomous_ai_safety:bestmatch\|A_autonomous_ai_safety:mostdownloaded`	48	98	325	12
The Authorization Boundary: Why MCP and AI Gateways Are Necessary—But Not Sufficient—for Regulated Agentic AI	`C_standards_conformance:bestmatch\|C_standards_conformance:mostdownloaded\|C_standards_conformance:mostrecent\|C_standards_conformance:mostviewed`	46	91	61	10	as ai agents transition from generating text to producing side effects—writing to databases, submitting regulatory filings, executing transactions&mdas...
Experiments for 'Runtime Monitoring for Markov Decision Processes'	`A_autonomous_ai_safety:bestmatch\|A_autonomous_ai_safety:mostdownloaded\|A_autonomous_ai_safety:mostviewed`	44	709	340	20
Control Barrier Functions in Multirotors: a Safety Filter for Obstacle Avoidance	`A_autonomous_ai_safety:bestmatch`	42	59	48	42
V-OCBF: Learning Safety Filters from Offline Data via Value-Guided Offline Control Barrier Functions	`A_autonomous_ai_safety:newest`	42	0	0	42
Explicit Control Barrier Function-based Safety Filters and their Resource-Aware Computation	`A_autonomous_ai_safety:newest`	42	0	0	42
Humans as Safety Constraints: A Survey of Human-in-the-Loop Reinforcement Learning for Critical Systems	`D_custom:mostrecent`	42	65	45	10	unlike traditional human-in-the-loop rl approaches that focus on learning efficiency, this work emphasizes human oversight to prevent catastrophic outcomes i...
D4.3 Runtime Assurance & Certification Framework – Final Release	`A_autonomous_ai_safety:bestmatch\|A_autonomous_ai_safety:mostrecent`	40	53	54	12
Remote Supervisory Control for a Robotic Container Handling System	`D_custom:bestmatch`	39	32	38	13	during the mmi platform meeting on the 8th of march 2022, tno colleagues represented moses project, by delivering a presentation entitled:  remote super...
Design and simulation of a TTRH-EV supervisory controller for a proton SAGA 1.3	`D_custom:bestmatch`	39	33	26	13	a supervisory controller design and implementation for retrofitted ttrh-ev saga is based on the bsfc map and ool of the engine.
Food safety management: preventive strategies and control of pathogenic microorganisms in food	`F_dsm_integration_structure:bestmatch\|F_dsm_integration_structure:mostdownloaded\|F_dsm_integration_structure:mostrecent\|F_dsm_integration_structure:mostviewed`	30	291	238	10	in this context, this review addresses food safety management as a preventive and control measure for pathogenic microorganisms in food, aiming to safeguard ...
Cutting Corners on Uncertainty: Zonotope Abstractions for Stream-based Runtime Monitoring	`A_autonomous_ai_safety:newest`	26	0	0	26
Towards transient frequency safety: A novel load frequency control with wind-storage system via control barrier function	`A_autonomous_ai_safety:newest\|C_standards_conformance:newest`	24	0	0	24
Resilient safety-critical control for autonomous electric vehicles via disturbance-observer-based adaptive control barrier functions	`A_autonomous_ai_safety:newest\|C_standards_conformance:newest`	24	0	0	24
Distributed Safety Critical Control among Uncontrollable Agents using Reconstructed Control Barrier Functions	`A_autonomous_ai_safety:newest`	24	0	0	24
Combinatorial Safety-Critical Coordination of Multi-Agent Systems via Mixed-Integer Responsibility Allocation and Control Barrier Functions	`A_autonomous_ai_safety:newest`	24	0	0	24
A Safety-Aware Shared Autonomy Framework with BarrierIK Using Control Barrier Functions	`A_autonomous_ai_safety:newest`	24	0	0	24
Learning Safety-Guaranteed, Non-Greedy Control Barrier Functions Using Reinforcement Learning	`A_autonomous_ai_safety:newest`	24	0	0	24
TTCBF: A Truncated Taylor Control Barrier Function for High-Order Safety Constraints	`A_autonomous_ai_safety:newest`	24	0	0	24
High Order Control Lyapunov Function - Control Barrier Function - Quadratic Programming Based Autonomous Driving Controller for Bicyclist Safety	`A_autonomous_ai_safety:newest`	24	0	0	24
A Speed-Constrained Sliding Mode Position Controller for PMLSM Based on Control Barrier Function	`A_autonomous_ai_safety:newest`	22	0	0	22
Distributed Safe Navigation of Multi-Agent Systems using Control Barrier Function-Based Optimal Controllers	`C_standards_conformance:newest`	22	0	0	22
Control Barrier Functions with Audio Risk Awareness for Robot Safe Navigation on Construction Sites	`A_autonomous_ai_safety:newest`	22	0	0	22

Top Seam Tells

Tell	Count
1	103
domain	86
safety	53
barrier function	43
control barrier function	41
gate+action+domain	38
safety filter	16
runtime monitor	13
runtime monitoring	12
runtime assurance	7

Note: Some sources do not provide abstracts/metrics; “tells” may be title-derived for those rows.

Near-Miss Diagnostics

Article	Bucket	Source	Tells	Views	DL	Why not candidate
Process Safety Management Gap Audit Reports in Steel Industry	`F_dsm_integration_structure`	zenodo	3	69	85	Near threshold
Process Safety Management Gap Audit Reports in Steel Industry	`F_dsm_integration_structure`	zenodo	3	69	85	Near threshold
Process Safety Management Gap Audit Reports in Steel Industry	`F_dsm_integration_structure`	zenodo	3	69	85	Near threshold
Process Safety Management Gap Audit Reports in Steel Industry	`F_dsm_integration_structure`	zenodo	3	69	85	Near threshold
From farm to fork: Enhancing meat traceability and safety with intelligent packaging	`A_autonomous_ai_safety`	crossref	3	0	0	No conversion; No metrics
Limitation and improvement of STPA-Sec for safety and security co-analysis	`F_dsm_integration_structure`	zenodo	2	310	2243	Near threshold
Limitation and improvement of STPA-Sec for safety and security co-analysis	`F_dsm_integration_structure`	zenodo	2	310	2243	Near threshold
Limitation and improvement of STPA-Sec for safety and security co-analysis	`F_dsm_integration_structure`	zenodo	2	310	2243	Near threshold
Safety of Perception System for Automated Driving: A Case Study on Apollo	`F_dsm_integration_structure`	zenodo	2	1172	847	Near threshold
Safety of Perception System for Automated Driving: A Case Study on Apollo	`F_dsm_integration_structure`	zenodo	2	1172	847	Near threshold
Safety of Perception System for Automated Driving: A Case Study on Apollo	`F_dsm_integration_structure`	zenodo	2	1172	847	Near threshold
Model-based safety validation of the automated driving function highway pilot	`F_dsm_integration_structure`	zenodo	2	182	839	Near threshold
Model-based safety validation of the automated driving function highway pilot	`F_dsm_integration_structure`	zenodo	2	182	839	Near threshold
Model-based safety validation of the automated driving function highway pilot	`F_dsm_integration_structure`	zenodo	2	182	839	Near threshold
Abhijeet Sarkar's The Superintelligence Blueprint: A Critical Analysis of AI Governance, Ethics, Strategic Foresight, Safety, Alignment, Arms Races, and Architectures	`D_custom`	zenodo	2	392	336	Near threshold
Abhijeet Sarkar's The Superintelligence Blueprint: A Critical Analysis of AI Governance, Ethics, Strategic Foresight, Safety, Alignment, Arms Races, and Architectures	`D_custom`	zenodo	2	392	336	Near threshold
Report of the Scientific Committee of the Spanish Agency for Consumer Affairs, Food Safety and Nutrition (AECOSAN) on the microbiological and allergenic risks associated with the consumption of insects	`F_dsm_integration_structure`	zenodo	2	285	270	Near threshold
Report of the Scientific Committee of the Spanish Agency for Consumer Affairs, Food Safety and Nutrition (AECOSAN) on the microbiological and allergenic risks associated with the consumption of insects	`F_dsm_integration_structure`	zenodo	2	285	270	Near threshold
Report of the Scientific Committee of the Spanish Agency for Consumer Affairs, Food Safety and Nutrition (AECOSAN) on the microbiological and allergenic risks associated with the consumption of insects	`F_dsm_integration_structure`	zenodo	2	285	270	Near threshold
Report of the Scientific Committee of the Spanish Agency for Consumer Affairs, Food Safety and Nutrition (AECOSAN) on the microbiological and allergenic risks associated with the consumption of insects	`F_dsm_integration_structure`	zenodo	2	285	270	Near threshold

Rows shown here are not final SEAM candidates, but they were close enough to help tune thresholds, buckets, and tell logic.

Why rows did not become SEAM candidates

reason	rows	share
Low SEAM score	9660	100.0%
No seam tells detected	7646	79.2%
No measurable conversion	4651	48.1%
No engagement metrics	4532	46.9%
Missing abstract / summary text	2	0.0%
Source likely sparse on abstract/metrics	2	0.0%

These are diagnostic reasons counted across non-candidate rows. A single row can contribute to more than one reason, so the shares are directional rather than additive.

Bucket Performance

bucket	rows	unique	text	tells	near	cand	cand_rate	med_views	med_dl
B_systems_resilience	1661	1017	1661	449	442	7	0.4%	10	5
A_autonomous_ai_safety	1750	1433	1750	413	344	69	3.9%	19	18
F_dsm_integration_structure	1750	1015	1750	346	339	7	0.4%	26	11
D_custom	1750	1404	1750	322	319	3	0.2%	16	12
C_standards_conformance	499	424	498	275	264	11	2.2%	0	0
I_authorization_gating	1750	1507	1750	183	179	4	0.2%	15.5	8
E_interface_icd	603	538	602	129	127	2	0.3%	0	0

Use this to see which buckets are producing rows, text, tells, near-misses, and candidates.

Source Performance

source	rows	unique	text	tells	near	cand	cand_rate	med_views	med_dl
zenodo	5184	2735	5184	927	892	35	0.7%	75	74
crossref	1750	1685	1750	449	432	17	1.0%	0	0
arxiv	1187	1167	1187	424	381	43	3.6%	0	0
openalex	1642	1573	1640	317	309	8	0.5%	0	0

Use this to compare which sources are providing richer data versus sparse metadata.

Top “New Keyword Candidates”

term	n	cand_rate	med_conv
A_autonomous_ai_safety	1750	3.9%	0.267
C_standards_conformance	499	2.2%	0.000
B_systems_resilience	1661	0.4%	0.300
F_dsm_integration_structure	1750	0.4%	0.191
E_interface_icd	603	0.3%	0.000
I_authorization_gating	1750	0.2%	0.246
D_custom	1750	0.2%	0.348

Heuristic: terms with high seam-candidate association (min 5 samples). Low-sample rows are highlighted and tooltipped.

Top “Exclude / Downweight Terms”

term	n	med_conv
E_interface_icd	84	0.500
C_standards_conformance	100	0.608
B_systems_resilience	1000	0.676
F_dsm_integration_structure	1000	0.818
I_authorization_gating	1000	0.875
D_custom	1000	0.959
A_autonomous_ai_safety	1000	1.015

Heuristic: Zenodo terms with low median conversion (min 10 samples, cutoff 0.02). Low-sample rows are highlighted and tooltipped.

Receipts

What these numbers mean

Engagement Comparison

Run Funnel

Bucket Yield

SEAM Candidate Articles

Top Seam Tells

Near-Miss Diagnostics

Why rows did not become SEAM candidates

Bucket Performance

Source Performance

Top “New Keyword Candidates”

Top “Exclude / Downweight Terms”

History and trends

Files

Stamp	Median Views	Median Downloads	Median Conv	Unique	SEAM Cand Rate
`20260309_111547`	9	4	0.104	7116	0.0%
`20260310_075703`	16	5	0.256	2623	0.0%
`20260313_082305`	9	3	0.099	7160	0.0%