```json { "scores": [ { "id": "cnv_3e97d61107684528", "score": 92, "tier": "great", "rationale": "Clear, concrete overview of dataset purpose and row structure. Essential orientation for first-time analyst." }, { "id": "cnv_a9eec7f367244494", "score": 78, "tier": "regular", "rationale": "Systematic column classification useful for understanding data structure, but lacks evidence queries and result tables." }, { "id": "cnv_b439610995154b36", "score": 72, "tier": "regular", "rationale": "Representative sample with concrete observations about demographics and response patterns. Useful but somewhat generic." }, { "id": "cnv_81f440c406d646af", "score": 65, "tier": "regular", "rationale": "Confirms data completeness (100% non-null). Important quality check but low-signal finding for clean dataset." }, { "id": "cnv_ee2a0ef135944c38", "score": 62, "tier": "regular", "rationale": "Confirms no duplicates. Necessary quality check but expected result for well-structured survey data." }, { "id": "cnv_ce90b6d624c744aa", "score": 68, "tier": "regular", "rationale": "Comprehensive cardinality breakdown across all columns. Useful reference but somewhat mechanical listing." }, { "id": "cnv_143b3a41df244f24", "score": 70, "tier": "regular", "rationale": "Distribution summaries for numeric columns with concrete ranges and means. Solid but expected for survey percentages." }, { "id": "cnv_f099d633b2c442ae", "score": 75, "tier": "regular", "rationale": "Thorough quality assessment confirming no outliers or format issues. Reassuring but not actionable for analysis." }, { "id": "cnv_dfe878e844974d24", "score": 73, "tier": "regular", "rationale": "Frequency breakdown of main categorical values with percentages. Useful reference but somewhat mechanical." }, { "id": "cnv_8cdf2b8acdad4841", "score": 80, "tier": "regular", "rationale": "Complete column reference with data types and meanings. Essential reference material but lacks evidence queries." }, { "id": "cnv_79f83a537d934e08", "score": 85, "tier": "great", "rationale": "Identifies strong correlations (r>0.90) between education/income/gender segments. Concrete, actionable insight about data structure." }, { "id": "cnv_5d301d4698dd4bd7", "score": 88, "tier": "great", "rationale": "Identifies key metric (Overall adoption) with specific extremes (78.70% none, 1.83% Perplexity). Concrete, substantive finding." }, { "id": "cnv_d24929a265fc4fd6", "score": 55, "tier": "not_useful", "rationale": "Correctly identifies no time dimension but lacks evidence queries. Somewhat obvious from dataset name." }, { "id": "cnv_8d80a9a8925e40b8", "score": 48, "tier": "not_useful", "rationale": "Redundant with previous time-dimension question. Confirms no trends but adds no new insight." }, { "id": "cnv_2a190de491ec4eb1", "score": 89, "tier": "great", "rationale": "Identifies education as key differentiator (62.33% Bachelor+ vs 47.16% HS adoption). Concrete, actionable demographic insight." }, { "id": "cnv_7ee59f3de8da462c", "score": 82, "tier": "regular", "rationale": "Maps natural segmentation by question themes and demographics. Useful for structuring analysis but somewhat descriptive." }, { "id": "cnv_b3a00b58d8854d18", "score": 84, "tier": "great", "rationale": "Concrete regional patterns (West leads adoption at 41.58% non-use vs Midwest 50.84%). Specific, actionable geographic insight." }, { "id": "cnv_b800c71eab204227", "score": 95, "tier": "great", "rationale": "Highly counterintuitive finding: lowest income (64.77%) outpaces highest income (57.70%) in AI adoption. Surprising, specific, decision-changing." }, { "id": "cnv_17bda91572ac4494", "score": 86, "tier": "great", "rationale": "Three concrete analytical questions with specific metrics (74.80% Software/IT vs 51.24% Healthcare). Actionable research directions." }, { "id": "cnv_636a39e3521a4034", "score": 76, "tier": "regular", "rationale": "Confirms 105 rows, 44 columns, July 2026 snapshot. Essential metadata but straightforward structural info." } ] } ```