Demiton · Schema
opportunity_win_probability contract v2
Predicted probability of winning a pipeline opportunity.
CompanyConstructionCivil EngineeringProject ManagementComplianceMCPArtificial IntelligenceOpen Contracting
Properties
| Name | Type | Description |
|---|---|---|
| p_win | number | Model-issued probability that the referenced pursuit is won. The shelf's only measure, already declared `PREDICTIVE`/`float`/`probability`. |
| n_wins | integer | Positive-class examples in the fit. |
| accuracy | number | Share of held-out decided opportunities classified correctly at the 0.5 threshold. |
| currency | currency | Currency the scored pursuit is denominated in; today stamped `"AUD"` unconditionally by the producer. |
| customer | string | The customer the pursuit is for, where one exists. |
| n_losses | integer | Negative-class examples in the fit. |
| scored_at | string | When this prediction was produced. |
| brier_score | number | Calibration error of the fit that issued these predictions, when a backtest was run. |
| valid_until | string | Until when this prediction is the current one for its pursuit. |
| model_version | string | Version tag of the issuing model. |
| feature_values | object | The five bounded feature inputs to the score: `value_band` (0–4), `has_customer`, `work_type_known`, `sales_cycle_known`, `log_value`. |
| training_as_of | string | The transaction-time cutoff the model was trained to; the label set is only decided opportunities known at this instant. |
| n_training_rows | integer | Decided (won/lost) opportunities the fit used; `MIN_TRAINING_ROWS = 5` gates whether any prediction is emitted. |
| subject_opportunity_ref | string | Stable identifier of the scored pursuit. |
JSON Schema
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "https://docs.demiton.io/registers/opportunity_win_probability/v2.json",
"title": "opportunity_win_probability contract v2",
"type": "object",
"required": [
"currency",
"model_version",
"n_losses",
"n_training_rows",
"n_wins",
"p_win",
"scored_at",
"subject_opportunity_ref",
"training_as_of"
],
"properties": {
"p_win": {
"type": "number",
"description": "Model-issued probability that the referenced pursuit is won. The shelf's only measure, already declared `PREDICTIVE`/`float`/`probability`.",
"x-demiton-requiredness": "required",
"x-demiton-unit": "probability 0–1"
},
"n_wins": {
"type": "integer",
"description": "Positive-class examples in the fit.",
"x-demiton-requiredness": "required",
"x-demiton-unit": "count"
},
"accuracy": {
"type": "number",
"description": "Share of held-out decided opportunities classified correctly at the 0.5 threshold.",
"x-demiton-requiredness": "optional",
"x-demiton-unit": "fraction 0–1"
},
"currency": {
"type": "currency",
"description": "Currency the scored pursuit is denominated in; today stamped `\"AUD\"` unconditionally by the producer.",
"x-demiton-requiredness": "required"
},
"customer": {
"type": "string",
"description": "The customer the pursuit is for, where one exists.",
"x-demiton-requiredness": "optional",
"x-demiton-reference": true
},
"n_losses": {
"type": "integer",
"description": "Negative-class examples in the fit.",
"x-demiton-requiredness": "required",
"x-demiton-unit": "count"
},
"scored_at": {
"type": "string",
"description": "When this prediction was produced.",
"x-demiton-requiredness": "required",
"x-demiton-unit": "UTC",
"format": "date-time",
"x-demiton-type": "datetime"
},
"brier_score": {
"type": "number",
"description": "Calibration error of the fit that issued these predictions, when a backtest was run.",
"x-demiton-requiredness": "optional",
"x-demiton-unit": "unitless (lower better)"
},
"valid_until": {
"type": "string",
"description": "Until when this prediction is the current one for its pursuit.",
"x-demiton-requiredness": "optional",
"x-demiton-unit": "UTC",
"format": "date-time",
"x-demiton-type": "datetime"
},
"model_version": {
"type": "string",
"description": "Version tag of the issuing model.",
"x-demiton-requiredness": "required"
},
"feature_values": {
"type": "object",
"description": "The five bounded feature inputs to the score: `value_band` (0–4), `has_customer`, `work_type_known`, `sales_cycle_known`, `log_value`.",
"x-demiton-requiredness": "optional"
},
"training_as_of": {
"type": "string",
"description": "The transaction-time cutoff the model was trained to; the label set is only decided opportunities known at this instant.",
"x-demiton-requiredness": "required",
"x-demiton-unit": "UTC",
"format": "date-time",
"x-demiton-type": "datetime"
},
"n_training_rows": {
"type": "integer",
"description": "Decided (won/lost) opportunities the fit used; `MIN_TRAINING_ROWS = 5` gates whether any prediction is emitted.",
"x-demiton-requiredness": "required",
"x-demiton-unit": "count"
},
"subject_opportunity_ref": {
"type": "string",
"description": "Stable identifier of the scored pursuit.",
"x-demiton-requiredness": "required"
}
},
"x-demiton-register-type": "opportunity_win_probability",
"x-demiton-contract-version": "2.0.1",
"x-demiton-store": "tenant",
"x-demiton-axes": [
{
"axis": "customer",
"requirement": "optional",
"role": "context"
},
{
"axis": "currency",
"requirement": "required",
"role": "context"
}
],
"x-demiton-measures": [
{
"key": "p_win",
"accumulation": "predictive",
"dtype": "float",
"unit": "probability"
}
],
"x-demiton-provenance": {
"standards": []
},
"description": "Predicted probability of winning a pipeline opportunity.",
"x-demiton-contract-url": "https://docs.demiton.io/registers/opportunity_win_probability/",
"x-demiton-register-catalog": "https://docs.demiton.io/concepts/register-catalog"
}
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