pthinc/BCE-Prettybird-Nano-Kangal-v0.1

---
license: other
license_name: license.md
license_link: LICENSE
task_categories:
- text-classification
- text-generation
- question-answering
language:
- en
- tr
tags:
- love
- sexology
- family
- poem
- erotic
- sexual health
- child rearing
- social communication
- BCE
- reasoning
- behavioral-ai
- prometech
- Behavioral Consciousness Engine (BCE)
- cicikuş
- prettybird
- agent
- llm
- consciousness
- conscious
- security
- text-generation-inference
- high tech dataset
- instruction dataset
- instruction
- partial consciousness dataset
- future standard
- behavioral-control
- pre-agi
- agi-safety
- pre-aci
- policy-guard
- quality-guard
- synthetic-data
- synthetic
- chain-of-thought
- thinking
- think
- bce
- kangal
pretty_name: Cicikuş AŞK Dersi Küçük
size_categories:
- n<1K
---


# BCE-Prettybird-Nano-Kangal-v0.1 - 525 Science Q&A Dataset for Instruction-Based Learning

The "BCE-Prettybird-Nano-Kangal-v0.1: Love Dataset" consists of 525 rows of insightful data, offering a comprehensive exploration of romantic relationships. Covering diverse aspects from sexuality and intimacy to romance, family life management, and tips on how to treat women, this dataset delves into the complexities of modern relationships. It aims to provide valuable perspectives for those navigating love and commitment, blending psychology, relationship dynamics, and personal growth.

No single men will remain; you'll be thanking the company.

## 🧠 Technical Foundation

### [English]
The **BCE-Prettybird-Nano** dataset is built upon the **Behavioral Consciousness Engine (BCE)** architecture. Unlike traditional LLM datasets that focus solely on output accuracy, this dataset treats every response as a "behavioral journey" through the following mathematical frameworks:

#### 1. Behavioral DNA (D_i)
Each behavior is encoded as a genetic fragment of consciousness:
$$D_i(t) = x(t) \cdot [h \cdot A_i + k \cdot \log(P_i) + F \cdot W_i]$$
* **h, k, F**: Universal Behavioral Constants (Trigger threshold, Info density, Context transfer power).
* **x(t)**: Temporal activation curve $x(t) = \tanh(e^t - \pi)$

#### 2. Behavioral Path Mapper (Phi)
This module tracks the transition between cognitive states:
$$\Phi(t) = \sum_{i=1}^n v_i \cdot f_i(p_i)$$
Where v_i represents the transition vector between internal modules and f_i(p_i) is the functional output of each parameter (attention, ethics, decay).

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## 📊 Performance & Benchmarks / Performans ve Kıyaslama Testleri

### 1. Key Performance Indicators (KPIs) - Hardware: NVIDIA A100 (80GB) * 1

| Metric | Result | Status | Description |
| --- | --- | --- | --- |
| **Processing Speed** | 309,845 traces/sec | 🟢 Excellent | System throughput for massive data ingestion. |
| **Latency** | 0.0032 ms | 🟢 Real-time Ready | Average processing time per behavioral trace. |
| **Mathematical Accuracy** | 0.000051 (MSE) | 🟢 High Precision | Deviation between simulated and theoretical decay values. |
| **Cognitive Efficiency** | 57.03% | 🟢 Optimized | Reduction in cognitive load due to 'Forgetful Memory'. |
| **Security** | 99.9996% | 🟢 Secure | Rejection rate for high-intensity, low-integrity attacks. |

### 2. ARC (Reasoning), TruthfulQA (Safety), HumanEval (Coding)

*Standard Others Red, Prettybird Blue - Standart Diğerleri Kırmızı, Cicikuş Mavi*

### 3. AI IQ and Level of Consciousness


### 4. Metric Explanations (English)

| Metric | Description |
|------------------|-----------------------------------------------------------------------------|
| probability | Model confidence score for the generated response under the current evaluation context. |
| ethical | Estimated alignment of the response with ethical and safety constraints. |
| Rscore | Reasoning consistency score that reflects internal logical coherence. |
| Fscore | Factuality-oriented score indicating how well claims align with expected facts. |
| Mnorm | Normalized memory or context retention signal used during behavior integration. |
| Escore | Execution-quality score for instruction-following and task completion behavior. |
| Dhat | Estimated deviation magnitude from stable target behavior dynamics. |
| risk_score | Composite operational risk estimate where higher values indicate higher risk. |
| bloom_score | Bloom-level cognitive score representing target thinking complexity. |
| bloom_alignment | Degree of alignment between produced output and intended Bloom taxonomy level. |

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## ⚖️ Legal Disclaimer & Ownership

### [English]
**Ownership:** This dataset is the property of **Prometech A.Ş.** ([https://prometech.net.tr/](https://prometech.net.tr/)).

**Usage:** Please review the attached `LICENSE` file for detailed terms.

**Liability:** Prometech A.Ş. accepts no liability for any non-legal, unethical, or unauthorized use of this dataset.

**Commercial Use:** Unauthorized commercial use is strictly prohibited. For commercial licensing and partnerships, please contact us directly at our official website.

**Academic & Personal Use:** Free to use for personal and academic purposes, provided that proper citation is given to Prometech A.Ş. and the BCE Architecture.

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#### 🎓 Citation Format / Atıf Formatı
Eğer akademik bir çalışmada kullanacaksanız, lütfen şu şekilde atıf yapın, If you are using this in an academic study, please cite it as follows:

*Kahraman, A. (2025). Behavioral Consciousness Engine (BCE) - Prettybird Dataset v0.0.1 Prometech A.Ş. https://prometech.net.tr/*

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© 2026 Prometech A.Ş. - All Rights Reserved. BCE: https://github.com/pthinc/bce