{
  "en": {
    "page_title": "ARG Detection System",
    "page_caption": "Antibiotic Resistance Gene Detection based on ESM-2 + CNN-Attention with CARD Integration",
    "sidebar_header": "About the System",
    "sidebar_pipeline": "**Pipeline:**\n1. Sequence: ESM-2 embedding\n2. CNN-Attention: Binary classification\n3. Cosine similarity: Top-3 CARD\n4. CARD metadata: Biological interpretation\n5. ESMFold: 3D structure visualization\n\n**Note:**\nThis system is for research and AMR surveillance only. Not for clinical diagnosis or therapy.",
    "sidebar_3d_toggle": "Show 3D visualization (ESMFold)",
    "sidebar_3d_caption": "Disable if connection is slow",
    "sidebar_lang_label": "Language / Bahasa",
    "mode_label": "Input mode:",
    "mode_manual": "📝 Manual sequence",
    "mode_upload": "📁 Upload File",
    "btn_example_arg": "Example ARG",
    "btn_example_non": "Example Non-ARG",
    "textarea_label": "Paste protein sequence (single-letter code):",
    "textarea_placeholder": "MAKIIFGENIAQLAESAGYDL...",
    "warning_invalid_chars": "Non-standard characters removed ({n} types)",
    "error_too_short": "Sequence too short (minimum {min} aa)",
    "input_manual_header": "Manual Input",
    "upload_label": "Upload protein sequence file:",
    "upload_help": "Supported formats: FASTA (.fasta, .fa, .faa), GenBank (.gb, .gbk), or plain text (.txt)",
    "upload_success": "{n} valid sequence(s) from {fmt} file",
    "upload_skipped": " ({skip} skipped, <{min} aa)",
    "upload_caption": "Detected format: *{fmt}* | File: {name}",
    "upload_error": "No valid sequences in {fmt} file. Make sure it contains protein sequences (not DNA/RNA) with minimum {min} aa.",
    "btn_predict": "Predict",
    "processing_header": "Processing {n} sequences...",
    "processing_status": "Processing {i}/{n}: {header}...",
    "processing_done": "Done!",
    "metric_classification": "Classification",
    "metric_confidence": "Confidence",
    "metric_length": "Sequence Length",
    "label_resistant": "RESISTANT",
    "label_non_resistant": "NON-RESISTANT",
    "result_resistant_msg": "This protein is predicted to contain an antibiotic resistance gene.",
    "result_non_resistant_msg": "This protein is predicted to not be an antibiotic resistance gene.",
    "truncated_msg": "Sequence truncated from {orig} to {new} aa",
    "stats_header": "**Sequence Statistics:**",
    "stat_hydrophobic": "Hydrophobic",
    "stat_positive": "Positive Charge",
    "stat_negative": "Negative Charge",
    "stat_aromatic": "Aromatic",
    "stat_polar": "Polar",
    "stat_top3_aa": "Top-3 AA",
    "attn_chart_title": "Attention Heatmap (Important positions for prediction)",
    "attn_xlabel": "Position (first {L} of {total} aa)",
    "attn_ylabel": "Attention Weight",
    "attn_interp_header": "**Attention Interpretation:**",
    "attn_dominant_text": "The model focuses most on the **{region}** region ({pct:.1f}% of total attention).",
    "attn_top5_text": "Top-5 highest positions: `{positions}`",
    "attn_caption": "Red = positions most attended by the model. Attention correlates with biologically important regions (correlation, not causation).",
    "3d_section_header": "#### 3D Protein Structure Prediction (ESMFold)",
    "3d_caption": "Structure predicted by ESMFold (Meta AI, 2022). Not an experimental structure (X-ray/cryo-EM validation needed).",
    "3d_no_pkg": "Package stmol/py3Dmol not available. Add stmol==0.0.9 and py3Dmol==2.0.4 to requirements.txt",
    "3d_too_long": "Sequence too long ({n} aa). ESMFold API is limited to 400 aa.",
    "3d_spinner": "Predicting 3D structure...",
    "3d_no_response": "ESMFold API not responding. Try again or disable 3D in the sidebar.",
    "3d_pos_caption": "Red positions (top-5 attention): {positions} | Rotate: right-click. Zoom: scroll.",
    "sim_header": "**Top-{k} Similar Proteins (CARD)**",
    "sim_expander": "View similarity details",
    "sim_chart_title": "Similarity Score vs CARD Bank",
    "sim_xlabel": "Cosine Similarity",
    "drug_header": "**Antibiotic Classes Potentially Affected:**",
    "btn_download_single": "Download Result",
    "btn_download_batch": "Download Results",
    "dl_title": "ARG Detection Result",
    "dl_divider": "====================",
    "dl_header_lbl": "Header",
    "dl_length_lbl": "Length",
    "dl_class_lbl": "Classification",
    "dl_conf_lbl": "Confidence",
    "dl_stats_section": "Sequence Statistics:",
    "dl_attn_section": "Attention Analysis:",
    "dl_dominant": "Dominant region",
    "dl_top5": "Top-5 positions",
    "dl_similar": "Top-{k} Similar Proteins (CARD):",
    "dl_disclaimer": "Disclaimer:\n  This result is for bioinformatics research purposes.\n  Not for clinical diagnosis or therapy.\n  Hanan Achmad | Hasanuddin University",
    "batch_header": "Batch Results Summary",
    "batch_metric_total": "Total Sequences",
    "batch_metric_resistant": "Predicted RESISTANT",
    "batch_metric_non_resistant": "Predicted NON-RESISTANT",
    "batch_summary_text": "**{n_res}/{n_tot} sequence(s) ({pct:.1f}%) predicted to contain antibiotic resistance genes.**",
    "batch_pie_title": "Prediction Distribution",
    "batch_expander": "View full table",
    "batch_cap_warning": "File contains {n} sequences. Only the first {cap} will be processed to prevent memory issues. Consider splitting the file.",
    "footer": "This system is for research and AMR surveillance. Not for clinical diagnosis. | Hanan Achmad | Hasanuddin University"
  },
  "id": {
    "page_title": "Sistem Deteksi ARG",
    "page_caption": "Deteksi Gen Resistensi Antibiotik berbasis ESM-2 + CNN-Attention dengan Integrasi CARD",
    "sidebar_header": "Tentang Sistem",
    "sidebar_pipeline": "**Pipeline:**\n1. Sekuens: Embedding ESM-2\n2. CNN-Attention: Klasifikasi biner\n3. Cosine similarity: Top-3 CARD\n4. Metadata CARD: Interpretasi biologis\n5. ESMFold: Visualisasi struktur 3D\n\n**Catatan:**\nSistem ini untuk penelitian dan surveilans AMR. Bukan untuk diagnosis atau terapi klinis.",
    "sidebar_3d_toggle": "Tampilkan visualisasi 3D (ESMFold)",
    "sidebar_3d_caption": "Nonaktifkan jika koneksi lambat",
    "sidebar_lang_label": "Language / Bahasa",
    "mode_label": "Mode input:",
    "mode_manual": "📝 Input sekuens manual",
    "mode_upload": "📁 Upload File",
    "btn_example_arg": "Contoh ARG",
    "btn_example_non": "Contoh Non-ARG",
    "textarea_label": "Tempel sekuens protein (single-letter code):",
    "textarea_placeholder": "MAKIIFGENIAQLAESAGYDL...",
    "warning_invalid_chars": "Karakter non-standard dihapus ({n} jenis)",
    "error_too_short": "Sekuens terlalu pendek (minimum {min} aa)",
    "input_manual_header": "Input Manual",
    "upload_label": "Upload file sekuens protein:",
    "upload_help": "Format yang didukung: FASTA (.fasta, .fa, .faa), GenBank (.gb, .gbk), atau plain text (.txt)",
    "upload_success": "{n} sekuens valid dari file {fmt}",
    "upload_skipped": " ({skip} dilewati karena <{min} aa)",
    "upload_caption": "Format terdeteksi: *{fmt}* | File: {name}",
    "upload_error": "Tidak ada sekuens valid di file {fmt}. Pastikan file berisi sekuens protein (bukan DNA/RNA) dengan panjang minimal {min} aa.",
    "btn_predict": "Prediksi",
    "processing_header": "Memproses {n} sekuens...",
    "processing_status": "Memproses {i}/{n}: {header}...",
    "processing_done": "Selesai!",
    "metric_classification": "Klasifikasi",
    "metric_confidence": "Keyakinan",
    "metric_length": "Panjang Sekuens",
    "label_resistant": "RESISTEN",
    "label_non_resistant": "TIDAK RESISTEN",
    "result_resistant_msg": "Protein ini diprediksi mengandung gen resistensi antibiotik.",
    "result_non_resistant_msg": "Protein ini diprediksi bukan gen resistensi antibiotik.",
    "truncated_msg": "Sekuens dipotong dari {orig} ke {new} aa",
    "stats_header": "**Statistik Sekuens:**",
    "stat_hydrophobic": "Hidrofobik",
    "stat_positive": "Muatan Positif",
    "stat_negative": "Muatan Negatif",
    "stat_aromatic": "Aromatik",
    "stat_polar": "Polar",
    "stat_top3_aa": "Top-3 AA",
    "attn_chart_title": "Attention Heatmap (Posisi penting untuk prediksi)",
    "attn_xlabel": "Posisi (pertama {L} dari {total} aa)",
    "attn_ylabel": "Bobot Attention",
    "attn_interp_header": "**Interpretasi Attention:**",
    "attn_dominant_text": "Model paling memperhatikan region **{region}** ({pct:.1f}% dari total attention).",
    "attn_top5_text": "Top-5 posisi tertinggi: `{positions}`",
    "attn_caption": "Warna merah = posisi paling diperhatikan model. Attention berkorelasi dengan region biologis penting (korelasi, bukan kausalitas).",
    "3d_section_header": "#### Prediksi Struktur 3D Protein (ESMFold)",
    "3d_caption": "Struktur diprediksi oleh ESMFold (Meta AI, 2022). Bukan struktur eksperimental (Perlu validasi X-ray/cryo-EM).",
    "3d_no_pkg": "Package stmol/py3Dmol tidak tersedia. Tambahkan stmol==0.0.9 dan py3Dmol==2.0.4 ke requirements.txt",
    "3d_too_long": "Sekuens terlalu panjang ({n} aa). ESMFold API dibatasi 400 aa.",
    "3d_spinner": "Memprediksi struktur 3D...",
    "3d_no_response": "ESMFold API tidak merespons. Coba lagi atau nonaktifkan 3D di sidebar.",
    "3d_pos_caption": "Posisi merah (top-5 attention): {positions} | Rotate: klik kanan. Zoom: scroll.",
    "sim_header": "**Top-{k} Protein Mirip (CARD)**",
    "sim_expander": "Lihat detail similarity",
    "sim_chart_title": "Similarity Score vs CARD Bank",
    "sim_xlabel": "Cosine Similarity",
    "drug_header": "**Kelas Antibiotik yang Mungkin Terdampak:**",
    "btn_download_single": "Download Hasil",
    "btn_download_batch": "Download Hasil",
    "dl_title": "Hasil Deteksi ARG",
    "dl_divider": "====================",
    "dl_header_lbl": "Header",
    "dl_length_lbl": "Panjang",
    "dl_class_lbl": "Klasifikasi",
    "dl_conf_lbl": "Keyakinan",
    "dl_stats_section": "Statistik Sekuens:",
    "dl_attn_section": "Analisis Attention:",
    "dl_dominant": "Region dominan",
    "dl_top5": "Top-5 posisi",
    "dl_similar": "Top-{k} Protein Mirip (CARD):",
    "dl_disclaimer": "Disclaimer:\n  Hasil ini untuk keperluan penelitian bioinformatika.\n  Bukan untuk diagnosis atau terapi klinis.\n  Hanan Achmad | Universitas Hasanuddin",
    "batch_header": "Ringkasan Hasil Batch",
    "batch_metric_total": "Total Sekuens",
    "batch_metric_resistant": "Prediksi RESISTEN",
    "batch_metric_non_resistant": "Prediksi TIDAK RESISTEN",
    "batch_summary_text": "**{n_res}/{n_tot} sekuens ({pct:.1f}%) diprediksi mengandung gen resistensi antibiotik.**",
    "batch_pie_title": "Distribusi Prediksi",
    "batch_expander": "Lihat tabel lengkap",
    "batch_cap_warning": "File berisi {n} sekuens. Hanya {cap} pertama yang akan diproses untuk mencegah kehabisan memori. Pertimbangkan untuk membagi file.",
    "footer": "Sistem ini untuk penelitian dan surveilans AMR. Bukan untuk diagnosis klinis. | Hanan Achmad | Universitas Hasanuddin"
  }
}