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EVALUATIONS & EVIDENCE

Evidence for the work ahead.

Explore verified customer reports and proposed evaluation protocols. Understand the dataset, execution source and limitations before comparing a score.

Verified evaluation reports

Customer-owned datasets, independently reviewed. Scores, billed USD and units are rechecked against completed platform requests. Fixture runs are explicitly labelled; these are not third-party benchmarks or universal model rankings.

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The following are proposed protocols, with no published protocol results. These original concepts have not been run. A protocol is not a model score or an independently validated benchmark.

3 protocols

ReasoningProposed

Reasoning review

Multi-step answers, explicit assumptions and factual consistency.

Protocol versionv0.1.0
ToolsProposed

Structured output

Schema adherence and validity of proposed tool arguments.

Protocol versionv0.1.0
VisionProposed

Visual understanding

Grounded answers about image content, with uncertainty made visible.

Protocol versionv0.1.0
PROPOSED EVALUATION · v0.1.0

Reasoning review

Assess whether an answer reaches a supported conclusion and exposes material uncertainty.

Dataset & version

Not published

A versioned set of self-contained reasoning tasks with reference answers and documented ambiguity. No dataset has been selected or published.

Evaluator & rubric

Proposed · evaluator version not published
  • Conclusion agrees with the verified reference answer.
  • Supporting statements are consistent with the supplied context.
  • Assumptions and ambiguous cases are identified without unsupported certainty.

Proposed prompt template

Template variables must be filled from a versioned dataset. This template has not been tested or used for a published run.

Task: {{task}}
Context: {{context}}
Give your answer with a concise justification based on the supplied information. State any assumptions and uncertainty.

Run configuration

Model version, route, sampling parameters and trial count are not set. Before execution:

  1. Freeze the dataset, prompt, model version and provider route before a run.
  2. Declare sampling parameters, permitted tools and repeated-trial count.
  3. Retain raw outputs, failures, usage units and USD costs for every request.
  4. Publish the evaluator version and uncertainty alongside reproducible evidence.