| openai / emoclassifiers Classifiers for "Investigating Affective Use and Emotional Well-being in ChatGPT" |
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0.7K json 0.5K py 0.1K md  0.1K gitignore JSONL 0.01K jsonl 0.01K txt
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| Standard analyses: | Main Code: 290 LOC (6 files) = PY (98%) + JSONL (1%) Secondary code: Test: 0 LOC (0); Generated: 0 LOC (0); Build & Deploy: 105 LOC (1); Other: 1,064 LOC (8); |
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| Duplication: 4% | |||
| File Size: 0% long (>1000 LOC), 100% short (<= 200 LOC) | |||
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Logical Component Decomposition: primary (2 components) | ||
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1 year, 3 months old
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0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
| Experimental analyses (less reliable heuristic analyses): | |||
| Unit Size: 0% long (>100 LOC), 100% short (<= 10 LOC) | |||
| Conditional Complexity: 0% complex (McCabe index > 50), 71% simple (McCabe index <= 5) | |||
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Static Component Dependencies: primary (2 components) | ||
Overall Activity Per Year
Latest commit date: 2025-07-03
Reference analysis date: 2026-06-24
activity per month, week and day...Per MonthLatest commit date: 2025-07-03
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Per DayLatest commit date: 2025-07-03
activity per month, week and day...Per MonthLatest commit date: 2025-07-03
Per WeekLatest commit date: 2025-07-03
Per DayLatest commit date: 2025-07-03
activity per month, week and day...Per MonthLatest commit date: 2025-07-03
Per WeekLatest commit date: 2025-07-03
Per DayLatest commit date: 2025-07-03
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