Datasets:

AgentsSci
/

IEEE2026_BigData_MAS-4-Science-Matching

# Datasheet

## Composition

The resource contains five scientific reasoning benchmarks, four core protocol
fixed evaluator where documented. Source problem records, generated messages,
outcomes, and deterministic interventional labels are separated into tables.

## Collection and filtering

LAB-Bench contains the project-defined `llm_strict` and `text_no_tool` text-only
slices. The broader slice must not be described as tool, retrieval, figure, or
supplementary-file use. Other benchmark slices follow the source files recorded
in the problem and run registries. Run coverage distinguishes the complete
source scope from the larger publication target, so filtered or pending cells
cannot be mistaken for a complete matrix.

ProtocolQA, and 600 SeqQA problems. FigQA and TableQA are excluded because they
carry required image assets. See `docs/labbench_filter_audit.md`.

## Limitations

Generated traces can contain model errors and long-form reasoning that should
not be treated as authoritative scientific advice. Runs outside the exact
publication matrix remain provisional until frozen source manifests and exact
problem-set validation are available. Request timestamps are unavailable, and
token accounting for unmeasured cells remains null rather than reconstructed.
The source staging includes legacy cost fields for supplemental GPT-OSS and
Gemma-3 slices. Because those slices lack validated per-trajectory accounting
and cost manifests, the release builder suppresses all six fields and records
the exact suppression count in the release manifest.
Client-observed wall time can be confounded by backend and run-batch conditions;
in particular, recovery cells on a different backend must not be read as clean
protocol-only latency comparisons.

## Recommended use

Use the resource for evaluation analysis, protocol comparison, trace browsing,
and research on interventional contribution labels. Honor each benchmark's
license and contamination policy before any training use.

	# Datasheet

	## Composition

	The resource contains five scientific reasoning benchmarks, four core protocol
	fixed evaluator where documented. Source problem records, generated messages,
	outcomes, and deterministic interventional labels are separated into tables.

	## Collection and filtering

	LAB-Bench contains the project-defined `llm_strict` and `text_no_tool` text-only
	slices. The broader slice must not be described as tool, retrieval, figure, or
	supplementary-file use. Other benchmark slices follow the source files recorded
	in the problem and run registries. Run coverage distinguishes the complete
	source scope from the larger publication target, so filtered or pending cells
	cannot be mistaken for a complete matrix.

	ProtocolQA, and 600 SeqQA problems. FigQA and TableQA are excluded because they
	carry required image assets. See `docs/labbench_filter_audit.md`.

	## Limitations

	Generated traces can contain model errors and long-form reasoning that should
	not be treated as authoritative scientific advice. Runs outside the exact
	publication matrix remain provisional until frozen source manifests and exact
	problem-set validation are available. Request timestamps are unavailable, and
	token accounting for unmeasured cells remains null rather than reconstructed.
	The source staging includes legacy cost fields for supplemental GPT-OSS and
	Gemma-3 slices. Because those slices lack validated per-trajectory accounting
	and cost manifests, the release builder suppresses all six fields and records
	the exact suppression count in the release manifest.
	Client-observed wall time can be confounded by backend and run-batch conditions;
	in particular, recovery cells on a different backend must not be read as clean
	protocol-only latency comparisons.

	## Recommended use

	Use the resource for evaluation analysis, protocol comparison, trace browsing,
	and research on interventional contribution labels. Honor each benchmark's
	license and contamination policy before any training use.