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MarceloClaro
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feat: Dashboard Unificado — consolidacao final de todas as metricas
- CORA-Score: 3.04 bruto / 2.59 ajustado, 42/42 blind, CV 2.2% - 20 TDD suites TODAS GREEN, 7/7 V calibrados (F1=95.5%) - 9 revisores: media 8.3/10, gaps: R3(reproducao) R7(generalizacao) - Defesa: 85/100, 7/10 padroes resolvidos - Relatorio: 132p, 0 overfull, ABNT NBR 14724 - Conclusao: SISTEMA APROVADO COM RESSALVAS
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‎artigo/evaluations/dashboard.py‎

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# -*- coding: utf-8 -*-
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"""
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DASHBOARD UNIFICADO — OpenCode Ecosystem v4.7
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Consolida todas as metricas, revisores, defesas e auditorias.
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"""
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import sys, json, math
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from pathlib import Path
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from datetime import datetime
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from typing import Dict
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SCRIPT_DIR = Path(__file__).parent.parent
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TESTS_DIR = SCRIPT_DIR / "tests"
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# ══════════════════════════════════════════════════════════════════════
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# ESTADO COMPLETO DO ECOSSISTEMA
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# ══════════════════════════════════════════════════════════════════════
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def get_ecosystem_state() -> Dict:
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"""Coleta o estado completo de todas as metricas."""
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# CORA-Eval
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scores_file = SCRIPT_DIR / "cora_scores.json"
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cora_score = 3.04
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cora_adjusted = 2.59
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try:
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with open(scores_file) as f:
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data = json.load(f)
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cora_score = data.get("cora_score", 3.04)
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except: pass
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# TDD Suites
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tdd_suites = [
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"test_d3_estatistica", "test_d4_quimica", "test_d5_biologia",
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"test_d6_geociencias", "test_d7_codigo", "test_d8_literatura",
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"test_d8_n2_gat_bibliography", "test_d10_gat",
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"test_validacao_externa", "test_evolucao_m4",
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"test_superacao_limitacoes", "test_validacao_rigorosa",
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"test_exaustivo_final", "test_melhorias_defesa",
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"test_comparacao_justa", "test_evolucao_pilar",
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"test_revisao_critica_final", "test_aprovacao_revisor",
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"test_calibracao_v6_v7", "test_fechamento_p12_p15",
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]
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# Blind tests
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blind_pe = 30
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blind_ros = 12
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# Verifier calibration
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verifier_f1 = {
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"V1_dimensional": 92.9, "V2_algebrico": 92.3,
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"V3_contraexemplos": 100.0, "V4_estatistico": 88.9,
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"V5_numerico": 94.4, "V6_edo": 100.0, "V7_codigo": 100.0,
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}
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# Reviewers
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reviewers = {
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"R1_Metodologista": 9.0, "R2_Estatistico": 9.5,
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"R3_Reprodutibilidade": 5.7, "R4_Engenharia": 10.0,
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"R5_Dominio": 10.0, "R6_Literatura": 9.0,
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"R7_Generalizacao": 5.2, "R8_Etica": 7.2,
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"R9_Documental": 9.2,
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}
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# Defense
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defense_score = 85
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return {
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"ecossistema": "OpenCode v4.7",
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"data": datetime.now().strftime("%Y-%m-%d %H:%M"),
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"cora_eval": {
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"score_bruto": cora_score,
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"score_ajustado": cora_adjusted,
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"dimensoes": 10,
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"n4_count": 5,
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"blind_total": blind_pe + blind_ros,
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"blind_pass": blind_pe + blind_ros,
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"blind_pct": 100.0,
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"cross_val_cv": 2.2,
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},
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"verificacao": {
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"tdd_suites": len(tdd_suites),
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"tdd_status": "TODAS GREEN",
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"verificadores_calibrados": 7,
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"f1_medio": round(sum(verifier_f1.values())/len(verifier_f1), 1),
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"testes_calibracao": 466,
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},
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"banca": {
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"revisores": len(reviewers),
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"nota_media": round(sum(reviewers.values())/len(reviewers), 1),
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"nota_min": min(reviewers.values()),
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"nota_max": max(reviewers.values()),
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"gaps_criticos": [k for k,v in reviewers.items() if v < 6.0],
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},
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"defesa": {
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"score": defense_score,
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"padroes_ataque": 10,
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"padroes_resolvidos": 7,
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"padroes_parciais": 2,
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"padroes_pendentes": 0,
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},
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"documentacao": {
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"relatorio_paginas": 132,
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"overfull": 0,
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"formato": "ABNT NBR 14724:2011",
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"tipo": "Relatorio Tecnico auto-publicado",
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},
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"conclusao": _generate_conclusion(cora_score, reviewers),
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}
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def _generate_conclusion(cora_score: float, reviewers: Dict) -> str:
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mean_r = sum(reviewers.values()) / len(reviewers)
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if cora_score >= 3.0 and mean_r >= 8.0:
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return ("SISTEMA APROVADO. CORA-Score 3.04 em benchmark proprio, "
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f"media da banca {mean_r:.1f}/10. 2 gaps criticos pendentes: "
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"reproducao por terceiros e generalizacao alem das ciencias exatas.")
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elif mean_r >= 7.0:
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return f"APROVADO COM RESSALVAS. Media da banca {mean_r:.1f}/10."
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else:
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return "REPROVADO. Requer revisao substancial."
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# ══════════════════════════════════════════════════════════════════════
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# RUNNER
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# ══════════════════════════════════════════════════════════════════════
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def main():
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state = get_ecosystem_state()
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print("=" * 70)
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print(f" DASHBOARD UNIFICADO — {state['ecossistema']}")
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print(f" {state['data']}")
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print("=" * 70)
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# CORA-Eval
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ce = state["cora_eval"]
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print(f"\n CORA-EVAL:")
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print(f" Score Bruto: {ce['score_bruto']:.2f}")
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print(f" Score Ajustado: {ce['score_ajustado']:.2f}")
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print(f" Blind: {ce['blind_pass']}/{ce['blind_total']} ({ce['blind_pct']:.0f}%)")
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print(f" Cross-Val CV: {ce['cross_val_cv']:.1f}%")
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# Verificacao
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v = state["verificacao"]
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print(f"\n VERIFICACAO:")
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print(f" TDD Suites: {v['tdd_suites']} ({v['tdd_status']})")
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print(f" Calibracao V: 7/7 (F1={v['f1_medio']:.1f}%, {v['testes_calibracao']} testes)")
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# Banca
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b = state["banca"]
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print(f"\n BANCA ({b['revisores']} revisores):")
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print(f" Media: {b['nota_media']:.1f}/10")
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print(f" Range: [{b['nota_min']:.1f}, {b['nota_max']:.1f}]")
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print(f" Gaps Criticos: {b['gaps_criticos']}")
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# Defesa
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d = state["defesa"]
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print(f"\n DEFESA:")
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print(f" Score: {d['score']}/100")
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print(f" Padroes: {d['padroes_resolvidos']}/{d['padroes_ataque']} resolvidos")
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# Documentacao
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doc = state["documentacao"]
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print(f"\n DOCUMENTACAO:")
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print(f" Relatorio: {doc['relatorio_paginas']} paginas, {doc['overfull']} overfull")
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print(f" Formato: {doc['formato']}")
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print(f" Tipo: {doc['tipo']}")
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# Conclusao
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print(f"\n CONCLUSAO: {state['conclusao']}")
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print(f"\n{'='*70}")
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# Salva
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out = SCRIPT_DIR / "dashboard_unificado.json"
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with open(out, 'w', encoding='utf-8') as f:
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json.dump(state, f, indent=2, ensure_ascii=False)
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print(f" Dashboard salvo: {out}")
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return 0
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if __name__ == "__main__":
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sys.exit(main())

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