{ "vercy": "1.0-draft", "publication": { "status": "research-draft", "adjudicationStatus": "unreviewed", "publishableCanonical": false, "generatedAt": "2026-09-12T10:34:56Z", "providers": [ "Codex" ], "breadth": "recalled by Codex without web access - no source was read", "missingProviders": [], "pass": 2, "cost": { "grok": { "seconds": 22.3, "error": "Reading additional input from stdin...\nOpenAI Codex v0.153.4\n--------\nworkdir: R:\\02_PROJECTS\\02_Meta_Models_Platforms\\Ver.cy\\current\\thing-registry-backlog\nmodel: gpt-6-astra\nprovider: openai\napproval: never\nsandbox: read-only\nreasoning effort: none\nreasoning summaries: none\nsession id: 01a0952e-3eb2-7e00-b1ef-5680d4b6ed38\n--------\nuser\nDescribe what is already known about one registered thing. Answer as JSON only, no prose around it.\n\nThing: irregularity\nSense to describe: not characterized by a fixed principle or rate; at irregular intervals\nDomain code: XCT.QLT\nAlso known as: (none)\n\n\nCont", "usd": 0.0, "recall": true }, "codex": { "seconds": 66.0, "error": "Reading additional input from stdin...\nOpenAI Codex v0.153.4\n--------\nworkdir: R:\\02_PROJECTS\\02_Meta_Models_Platforms\\Ver.cy\\current\\thing-registry-backlog\nmodel: gpt-6-astra\nprovider: openai\napproval: never\nsandbox: read-only\nreasoning effort: none\nreasoning summaries: none\nsession id: 01a0952e-3eb5-7a82-9f7d-5b8658e6943b\n--------\nuser\nYou are drafting a Vercy meta-model for one registered thing. Answer as JSON only, no prose around it.\n\nThing: irregularity\nRegistry id: vr.tr.irregularity\nPlane / domain: XCT / XCT.QLT\nRegistry definition: not characterized by a fixed principle or rate; at ir" } }, "enrichment": { "pass": 3, "engine": "claude", "producedAt": "2026-10-06T11:00:00Z", "ingestedAt": "2026-10-06T08:02:29+00:00", "fields": [ "agent_conduct", "ethics", "failure_modes_and_hazards", "owners" ] }, "gate": { "passed": true, "version": "1.0", "at": "2026-10-07T12:16:27+00:00", "evidence": [ "completeness 1.00", "sense: WordNet gloss", "2 live sources", "review by codex: pass" ] } }, "metaModel": { "id": "THING-IRREGULARITY", "registryId": "vr.tr.irregularity", "name": "irregularity", "version": "0.1.0-research.1", "entryKind": "thing", "family": "Thing Registry", "domain": [ "XCT.QLT" ], "status": "research-draft" }, "canonicalUrl": "https://ver.cy/models/thing/irregularity/", "model": { "registry_id": "vr.tr.irregularity", "name": "irregularity", "purpose": "Enable an agent to recognise, assess and respond to irregularity by recording what lacks a fixed principle or rate, against which expectation, and within what observational limits.", "definition": "Irregularity is the quality of a pattern, process, or sequence that does not conform to a specified regular rule, constant rate, or uniform spacing of occurrences.", "scope_statement": "This model owns irregularity as a contextual quality of an observed arrangement, sequence or process, including departures from a specified organising principle and unequal intervals between occurrences; it does not presume randomness, defect or wrongdoing.", "in_scope": [ "The arrangement, sequence or process described as irregular and the aspect being assessed", "The fixed principle, rate or interval pattern used as a reference", "Observed departures, their magnitude and their distribution", "Dependence of an irregularity judgment on scale, observation window and tolerance", "Evidence supporting the judgment and limits on interpretation", "Conditions for monitoring, investigating or accommodating irregularity" ], "out_of_scope": [ "Complete models of the objects or processes that exhibit irregularity", "Randomness and stochastic mechanisms as independent concepts", "Legal violations, procedural noncompliance and moral wrongdoing", "Disease diagnoses or equipment fault diagnoses", "Statistical outlier detection methods as standalone models", "Geometric shape descriptions unrelated to an assessed organising principle" ], "distinguishing_features": [ "Ask whether occurrences have unequal spacing or a changing rate: a sequence can be sparse yet regular if its intervals remain fixed.", "Ask whether the judgment concerns recurrence or organisation rather than mere unusualness: an uncommon pattern may still be regular.", "Ask whether unpredictability has actually been established: unequal intervals alone do not show that a sequence is random or lacks a deterministic rule.", "Ask whether the apparent departure persists after accounting for measurement precision, missed observations and the chosen observation window.", "Ask whether a relevant rule was violated: describing a pattern as irregular does not by itself establish defect, harm or noncompliance." ], "characteristics": [ { "name": "Bearer and assessed aspect", "kind": "relation", "unit_or_values": "Reference to a sequence, process or arrangement and its timing, rate, spacing or organisation", "why_it_matters": "A bearer may be regular in one aspect and irregular in another." }, { "name": "Interpretation of irregularity", "kind": "category", "unit_or_values": "Unequal intervals; variable rate; departure from a specified organising principle; no principle established within the investigation", "why_it_matters": "Separates measurable departures from a limited failure to identify a rule." }, { "name": "Reference regularity", "kind": "relation", "unit_or_values": "Named principle, expected interval, expected rate or comparison pattern, with its origin", "why_it_matters": "Makes the basis of the judgment explicit and open to challenge." }, { "name": "Assessment extent", "kind": "measurement", "unit_or_values": "Observation start and end, spatial extent or index range, with resolution and relevant units", "why_it_matters": "Regularity judgments can change when the observation extent or resolution changes." }, { "name": "Departure magnitude", "kind": "measurement", "unit_or_values": "Deviation from the reference in native units or a named dimensionless measure", "why_it_matters": "Distinguishes small tolerated variation from departures relevant to the task." }, { "name": "Distribution of departures", "kind": "category", "unit_or_values": "Isolated; clustered; alternating; drifting; widespread; unresolved", "why_it_matters": "Guides investigation without assuming that every departure has the same explanation." }, { "name": "Assessment tolerance", "kind": "measurement", "unit_or_values": "Permitted deviation in native units or relative terms, with justification", "why_it_matters": "Determines when observed variation changes the classification." }, { "name": "Assessment state", "kind": "state", "unit_or_values": "Supported within stated limits; provisional; contested; insufficient observations", "why_it_matters": "Prevents a limited observation from becoming an unrestricted claim about the bearer." } ], "affordances": [ "Compare observed intervals, rates or arrangements with an explicit reference regularity.", "Locate departures and describe their magnitude and distribution.", "Reassess irregularity under different windows, resolutions and tolerances.", "Investigate whether missed observations or overlapping regular processes explain the appearance.", "Choose whether to monitor, investigate or accommodate the variation according to its consequences.", "Communicate the judgment with its reference, evidence and unresolved alternatives." ], "agent_conduct": { "may": [ "Detect and report departures from an expected pattern or rate in data it is authorized to analyse.", "State which rule or rate the irregularity is measured against." ], "must_not": [ "Treat an irregularity as proof of fraud or fault without investigation.", "Flag people as suspicious based on irregular but lawful behaviour.", "Hide irregularities in safety or financial data.", "Smooth or delete irregular readings without recording it." ], "requires_human": [ "Acting against a person or account because of a detected irregularity." ] }, "ethics": { "considerations": [ "Anomaly flags can wrongly target people with unusual but innocent lives.", "Hidden irregularities in safety data can cost lives." ], "affected_parties": [ "People flagged by systems", "Auditors", "Users of the data" ] }, "owners": { "steward": "Nobody: a quality of patterns; the owner of a dataset answers for what is flagged.", "master_systems": [] }, "failure_modes_and_hazards": [ "False positives that lead to unfair suspicion.", "Missed real faults when irregular readings are discarded." ], "what_it_is_for": [ "Irregularity is encountered when observed timing, spacing, shape or behavior departs from an expected pattern.", "It is used in monitoring, quality assessment and data analysis to describe departures that require interpretation against a stated rule or baseline." ], "facets_not_applicable": { "interfaces": "No single standard, law or official classification applies to irregularity as a general quality across domains.", "recognition": "Irregularity is an abstract quality established by comparison with a rule or baseline rather than a thing with its own visual identity." } }, "sources": [ { "id": "oewn", "title": "Open English WordNet 2024, synset oewn-04777450-n", "url": "https://en-word.net/id/oewn-04777450-n", "what_it_supports": "sense and gloss of the concept", "url_status": "live", "checked_by": "http 200" }, { "id": "wiktionary-en", "title": "Wiktionary: irregularity", "url": "https://en.wiktionary.org/wiki/irregularity", "what_it_supports": "word senses and usage", "url_status": "live", "checked_by": "http 200" } ], "structure": { "bundles": [ { "id": "meaning-and-reference", "name": "Meaning and reference", "description": "Establish what irregularity means in this assessment and what regularity would look like.", "rationale": "The registry definition includes both lack of a fixed principle and occurrence at irregular intervals; these require distinct tests.", "layers": [ { "id": "assessed-sense", "name": "Assessed sense", "description": "Identify the bearer, aspect and interpretation to which the judgment applies.", "findings": [ { "id": "aspect-specific-irregularity", "name": "Aspect-specific irregularity", "description": "Record whether the claim concerns intervals, rate or organisation, without extending it to every property of the bearer.", "questions": [ { "text": "What exactly is irregular: occurrence times, rate, spacing or adherence to an organising principle?", "kind": "definition", "id": "aspect-specific-irregularity-q01" }, { "text": "Which aspects of the same bearer remain regular or have not been assessed?", "kind": "boundary", "id": "aspect-specific-irregularity-q02" } ] } ] }, { "id": "reference-selection", "name": "Reference selection", "description": "Make the expected principle or rate and the authority for choosing it explicit.", "findings": [ { "id": "reference-and-its-origin", "name": "Reference and its origin", "description": "Record whether regularity is defined by an imposed schedule, a proposed rule, past observations or another stated convention.", "questions": [ { "text": "What fixed principle, interval or rate would make this observation count as regular?", "kind": "definition", "id": "reference-and-its-origin-q01" }, { "text": "Who or what supplied that reference, and where is its justification recorded?", "kind": "provenance", "id": "reference-and-its-origin-q02" }, { "text": "Would another defensible reference change the judgment?", "kind": "boundary", "id": "reference-and-its-origin-q03" } ] } ] } ] }, { "id": "departures-and-patterns", "name": "Departures and patterns", "description": "Describe the observable form and degree of departure from regularity.", "rationale": "An irregularity label alone cannot distinguish unequal gaps, changing rates and failures of a proposed organising rule.", "layers": [ { "id": "interval-and-rate-variation", "name": "Interval and rate variation", "description": "Assess the spacing of occurrences separately from rates calculated over windows.", "findings": [ { "id": "unequal-gaps-and-windowed-rates", "name": "Unequal gaps and windowed rates", "description": "Record event intervals and windowed rates so that an average does not conceal the variation being assessed.", "questions": [ { "text": "What are the observed intervals between successive occurrences, and in which units?", "kind": "measurement", "id": "unequal-gaps-and-windowed-rates-q01" }, { "text": "How do calculated rates change with the size and placement of the counting window?", "kind": "measurement", "id": "unequal-gaps-and-windowed-rates-q02" }, { "text": "What variation exceeds the stated tolerance for regular occurrence?", "kind": "boundary", "id": "unequal-gaps-and-windowed-rates-q03" } ] } ] }, { "id": "organising-rule-departures", "name": "Organising rule departures", "description": "Assess where and how an arrangement or sequence departs from a specified principle.", "findings": [ { "id": "departure-location-and-magnitude", "name": "Departure location and magnitude", "description": "Record the positions, sizes and grouping of departures rather than treating every irregular pattern as equivalent.", "questions": [ { "text": "Which observations fail the proposed organising rule, and by how much where a magnitude is meaningful?", "kind": "measurement", "id": "departure-location-and-magnitude-q01" }, { "text": "Are departures isolated, clustered, alternating, drifting or distributed throughout the assessed extent?", "kind": "measurement", "id": "departure-location-and-magnitude-q02" }, { "text": "Does a repeating pattern of departures suggest a different regularity that should be tested?", "kind": "boundary", "id": "departure-location-and-magnitude-q03" } ] } ] } ] }, { "id": "observation-and-alternatives", "name": "Observation and alternatives", "description": "Test whether apparent irregularity survives scrutiny of observation conditions and alternative descriptions.", "rationale": "Incomplete sampling and an unsuitable reference can produce an irregularity judgment that the underlying evidence does not sustain.", "layers": [ { "id": "observation-adequacy", "name": "Observation adequacy", "description": "Assess coverage, precision and segmentation of the evidence.", "findings": [ { "id": "coverage-and-resolution-limits", "name": "Coverage and resolution limits", "description": "Record whether missing events, rounding, detection thresholds or short observation spans could account for apparent departures.", "questions": [ { "text": "How were occurrences or positions captured, and which observations may be missing or imprecise?", "kind": "provenance", "id": "coverage-and-resolution-limits-q01" }, { "text": "Does the irregularity judgment persist across plausible corrections and changes in resolution or observation extent?", "kind": "measurement", "id": "coverage-and-resolution-limits-q02" } ] } ] }, { "id": "alternative-explanations", "name": "Alternative explanations", "description": "Separate observed variation from claims about randomness or the absence of any rule.", "findings": [ { "id": "unidentified-rule-versus-no-rule", "name": "Unidentified rule versus no rule", "description": "Record tested alternatives and distinguish failure to identify a principle from a justified claim about the limits of possible principles.", "questions": [ { "text": "Could a changing schedule, overlapping regular sequences or a deterministic variable-interval rule account for the observations?", "kind": "boundary", "id": "unidentified-rule-versus-no-rule-q01" }, { "text": "Which alternative rules have actually been examined, using what evidence?", "kind": "provenance", "id": "unidentified-rule-versus-no-rule-q02" }, { "text": "What further observation would discriminate among the remaining interpretations?", "kind": "action", "id": "unidentified-rule-versus-no-rule-q03" } ] } ] } ] }, { "id": "judgment-and-response", "name": "Judgment and response", "description": "Turn a qualified irregularity assessment into an appropriate decision.", "rationale": "Irregularity may be tolerable or consequential; the observed departure alone does not determine what should be done.", "layers": [ { "id": "classification-boundaries", "name": "Classification boundaries", "description": "Record the decision threshold and keep descriptive irregularity separate from neighbouring judgments.", "findings": [ { "id": "tolerance-and-interpretive-limits", "name": "Tolerance and interpretive limits", "description": "State when variation warrants the label and what additional evidence would be needed to classify it as a fault, anomaly or violation.", "questions": [ { "text": "Why is the selected tolerance appropriate for this task and observation precision?", "kind": "boundary", "id": "tolerance-and-interpretive-limits-q01" }, { "text": "What independent criterion, if any, makes this irregularity a defect, anomaly or rule violation?", "kind": "boundary", "id": "tolerance-and-interpretive-limits-q02" } ] } ] }, { "id": "response-and-reassessment", "name": "Response and reassessment", "description": "Connect the assessment to practical consequences and explicit review conditions.", "findings": [ { "id": "consequence-based-response", "name": "Consequence-based response", "description": "Record whether the observed variation calls for accommodation, monitoring or investigation, and when that choice should be revisited.", "questions": [ { "text": "Which observed or anticipated consequence justifies accommodating, monitoring or investigating this irregularity?", "kind": "action", "id": "consequence-based-response-q01" }, { "text": "What change in departure magnitude, distribution or evidence would trigger reassessment?", "kind": "action", "id": "consequence-based-response-q02" }, { "text": "What reference, observation limits and unresolved alternatives must accompany the communicated judgment?", "kind": "provenance", "id": "consequence-based-response-q03" } ] } ] } ] }, { "id": "evidence-and-external-alignment", "name": "Evidence and external alignment", "description": "What the world already says about this thing, gathered so the model can be checked against it.", "rationale": "A model that cannot be lined up against existing standards, identifiers and practice cannot be adopted by anyone who already uses them.", "layers": [ { "id": "reported-evidence", "name": "Reported evidence", "description": "Findings from the breadth pass, kept separate from the structural claims.", "findings": [ { "id": "evidence-confidence-notes", "name": "Check these first", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ "This is a general descriptive quality, not a single standardized technical construct with a universal metric.", "Any operational definition should specify the relevant rule or rate, observation timescale, and tolerated deviation.", "The intended sense excludes administrative wrongdoing, geometric unevenness, and domain-specific mathematical meanings of irregularity." ], "questions": [ { "id": "evidence-confidence-notes-q01", "text": "Which of these check these first hold for the sense of irregularity this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-kinds", "name": "Kinds and varieties", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ "Unequal intervals between occurrences", "Variation in rate over time", "Nonperiodic recurrence", "Departures from an otherwise regular pattern" ], "questions": [ { "id": "evidence-kinds-q01", "text": "Which of these kinds and varieties hold for the sense of irregularity this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-real-world-use", "name": "Real-world use", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ "Describing observations collected at unequal time intervals", "Characterizing uneven arrivals or service demand", "Assessing departures from regular production or delivery schedules", "Describing variation in the timing of biological rhythms" ], "questions": [ { "id": "evidence-real-world-use-q01", "text": "Which of these real-world use hold for the sense of irregularity this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-measurements", "name": "Typical measurements", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ { "quantity": "Inter-event interval", "typical_range": "Positive durations; no universal typical range", "unit": "Time units appropriate to the process" }, { "quantity": "Coefficient of variation of inter-event intervals", "typical_range": "Nonnegative when defined; zero indicates equal intervals, with no universal threshold for irregularity", "unit": "Dimensionless" }, { "quantity": "Deviation from scheduled occurrence time", "typical_range": "Context-dependent; requires a reference schedule", "unit": "Time units appropriate to the process" } ], "questions": [ { "id": "evidence-measurements-q01", "text": "Which of these typical measurements hold for the sense of irregularity this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-failure-modes-and-hazards", "name": "Failure modes and hazards", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ "Equating irregularity with randomness even when a deterministic mechanism produces the pattern", "Inferring irregularity from missing observations, timestamp errors, or inadequate sampling", "Treating a variable rate as irregular without checking whether its variation follows a regular cycle", "Applying an irregularity label without specifying the reference rule, tolerance, and observation timescale", "Assuming uniform sampling when analyzing irregularly timed measurements" ], "questions": [ { "id": "evidence-failure-modes-and-hazards-q01", "text": "Which of these failure modes and hazards hold for the sense of irregularity this model covers, and on what evidence?", "kind": "provenance" } ] }, { "id": "evidence-neighbours", "name": "Neighbouring kinds and how to tell them apart", "description": "Recalled without web access and unsourced; every item is a lead to verify.", "evidence": [ { "name": "Randomness", "difference": "Randomness concerns chance or probabilistic structure; irregularity concerns departures from regularity and can occur in deterministic sequences." }, { "name": "Variability", "difference": "Variability means values differ; those differences may follow a perfectly regular pattern." }, { "name": "Aperiodicity", "difference": "Aperiodicity specifically excludes exact periodic repetition; irregularity can describe unequal local intervals within a repeating larger pattern." }, { "name": "Intermittency", "difference": "Intermittency means activity alternates with inactivity; these alternations can occur at regular intervals." }, { "name": "Unpredictability", "difference": "Unpredictability concerns limits on forecasting; unequal intervals can be fully specified and predictable." }, { "name": "Noncompliance", "difference": "Noncompliance is failure to meet a prescribed requirement; irregular timing alone need not violate any requirement." } ], "questions": [ { "id": "evidence-neighbours-q01", "text": "Which of these neighbouring kinds and how to tell them apart hold for the sense of irregularity this model covers, and on what evidence?", "kind": "provenance" } ] } ] } ] } ] }, "openQuestions": [ "Which reference works and disciplinary uses distinguish irregular intervals from the broader absence of a fixed principle, and where do their definitions disagree?", "Does the registry intend spatial and organisational irregularity to fall within this entry, and how should those uses connect to neighbouring quality models?", "Which operational measures are appropriate for different bearers, and under what assumptions can their results be compared?", "What observation coverage and uncertainty treatment are sufficient to support an irregularity judgment in each intended application?", "How should the model represent sequences that follow a deterministic rule but have unequal intervals, especially when users disagree about whether they are regular?" ], "statistics": { "bundles": 5, "layers": 9, "findings": 14, "questions": 27 } }