{
  "schema_version": "1.0",
  "generator": {
    "name": "PlayChessOnline Position Review Generator",
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    "generated_at_utc": "2026-10-23T07:00:58.953646+00:00",
    "runtime_seconds": 12.350063,
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    "platform": "Windows-10-10.0.19045-SP0"
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    "slug": "kostic-pastar-knight-jump",
    "title": "Kostic vs Pastar: three choices between simplicity and complications",
    "source": {
      "label": "Knight Jump article and public Lichess study",
      "url": "https://knight-jump.com/blog/and-the-rapid-games-we-lost"
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    {
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    {
      "id": "turning-point-16",
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        "safety_threshold_cp": 100,
        "observed_distinct_model_moves": 1,
        "safe_distinct_model_moves": 0,
        "passes": false
      },
      "models": [
        {
          "key": "v6_active",
          "label": "V6 Active",
          "intended_profile": "active, initiative-seeking",
          "top_move": {
            "uci": "d5f3",
            "san": "Qxf3",
            "hybrid_score_cp": 227.86041
          },
          "top_three": [
            {
              "uci": "d5f3",
              "san": "Qxf3",
              "hybrid_score_cp": 227.86041
            },
            {
              "uci": "d5b3",
              "san": "Qxb3",
              "hybrid_score_cp": 69.263114
            },
            {
              "uci": "a7a5",
              "san": "a5",
              "hybrid_score_cp": -2.56129
            }
          ]
        },
        {
          "key": "v8_sharp",
          "label": "V8 Sharp",
          "intended_profile": "sharp club-player profile on curated data",
          "top_move": {
            "uci": "d5f3",
            "san": "Qxf3",
            "hybrid_score_cp": 227.235445
          },
          "top_three": [
            {
              "uci": "d5f3",
              "san": "Qxf3",
              "hybrid_score_cp": 227.235445
            },
            {
              "uci": "d5b3",
              "san": "Qxb3",
              "hybrid_score_cp": 68.938813
            },
            {
              "uci": "a7a5",
              "san": "a5",
              "hybrid_score_cp": -3.156447
            }
          ]
        },
        {
          "key": "v9_positional",
          "label": "V9 Positional",
          "intended_profile": "calm positional pressure",
          "top_move": {
            "uci": "d5f3",
            "san": "Qxf3",
            "hybrid_score_cp": 226.270381
          },
          "top_three": [
            {
              "uci": "d5f3",
              "san": "Qxf3",
              "hybrid_score_cp": 226.270381
            },
            {
              "uci": "d5b3",
              "san": "Qxb3",
              "hybrid_score_cp": 68.901671
            },
            {
              "uci": "a7a5",
              "san": "a5",
              "hybrid_score_cp": -2.671326
            }
          ]
        },
        {
          "key": "v15_endgame",
          "label": "V15 Endgame",
          "intended_profile": "endgame-focused distilled evaluator",
          "top_move": {
            "uci": "d5f3",
            "san": "Qxf3",
            "hybrid_score_cp": 227.774551
          },
          "top_three": [
            {
              "uci": "d5f3",
              "san": "Qxf3",
              "hybrid_score_cp": 227.774551
            },
            {
              "uci": "d5b3",
              "san": "Qxb3",
              "hybrid_score_cp": 75.072831
            },
            {
              "uci": "a8b8",
              "san": "Rab8",
              "hybrid_score_cp": 5.720837
            }
          ]
        },
        {
          "key": "v17_file_pressure",
          "label": "V17 File Pressure",
          "intended_profile": "open-file and rook-pressure weighting",
          "top_move": {
            "uci": "d5f3",
            "san": "Qxf3",
            "hybrid_score_cp": 228.674895
          },
          "top_three": [
            {
              "uci": "d5f3",
              "san": "Qxf3",
              "hybrid_score_cp": 228.674895
            },
            {
              "uci": "d5b3",
              "san": "Qxb3",
              "hybrid_score_cp": 69.908325
            },
            {
              "uci": "d5d8",
              "san": "Qd8",
              "hybrid_score_cp": -1.673755
            }
          ]
        },
        {
          "key": "v18_defensive",
          "label": "V18 Defensive",
          "intended_profile": "defensive tension and counterpunch weighting",
          "top_move": {
            "uci": "d5f3",
            "san": "Qxf3",
            "hybrid_score_cp": 232.127971
          },
          "top_three": [
            {
              "uci": "d5f3",
              "san": "Qxf3",
              "hybrid_score_cp": 232.127971
            },
            {
              "uci": "d5b3",
              "san": "Qxb3",
              "hybrid_score_cp": 70.739237
            },
            {
              "uci": "d5d8",
              "san": "Qd8",
              "hybrid_score_cp": -0.998386
            }
          ]
        }
      ],
      "stockfish": {
        "best_move": {
          "uci": "e7f6",
          "san": "Bf6"
        },
        "best_score": {
          "centipawns": -31,
          "is_mate": false,
          "mate_in": null,
          "comparison_cp": -31
        },
        "best_pv": {
          "uci": [
            "e7f6",
            "c1c7",
            "a8c8",
            "f3h4",
            "c8c7",
            "g2d5",
            "b7d5",
            "h4f3",
            "c7c2",
            "f3d4",
            "f6d4",
            "g4d4",
            "c2e2",
            "d4a4",
            "h7h6"
          ],
          "san": "16...Bf6 17. Rc7 Rac8 18. Nh4 Rxc7 19. Bxd5 Bxd5 20. Nf3 Rc2 21. Nxd4 Bxd4 22. Qxd4 Rxe2 23. Qa4 h6"
        },
        "nodes": 250032,
        "depth": 16,
        "seldepth": 17,
        "verified_choices": [
          {
            "move": {
              "uci": "d5f3",
              "san": "Qxf3"
            },
            "is_played_move": false,
            "is_engine_best_move": false,
            "selected_by_models": [
              "V15 Endgame",
              "V17 File Pressure",
              "V18 Defensive",
              "V6 Active",
              "V8 Sharp",
              "V9 Positional"
            ],
            "score": {
              "centipawns": -574,
              "is_mate": false,
              "mate_in": null,
              "comparison_cp": -574
            },
            "loss_cp": 543,
            "within_100cp": false,
            "within_200cp": false,
            "pv": {
              "uci": [
                "d5f3",
                "g2f3",
                "b7f3",
                "g4f3",
                "e7a3",
                "c1c6",
                "a8c8",
                "g1h1",
                "c8c6",
                "f3c6",
                "f8b8",
                "c6c4",
                "b6b5",
                "c4c6",
                "a3f8",
                "a2a4",
                "b8b6"
              ],
              "san": "16...Qxf3 17. Bxf3 Bxf3 18. Qxf3 Ba3 19. Rc6 Rac8 20. Kh1 Rxc6 21. Qxc6 Rb8 22. Qc4 b5 23. Qc6 Bf8 24. a4 Rb6"
            },
            "nodes": 250455,
            "depth": 15,
            "seldepth": 23
          },
          {
            "move": {
              "uci": "e7c5",
              "san": "Bc5"
            },
            "is_played_move": true,
            "is_engine_best_move": false,
            "selected_by_models": [],
            "score": {
              "centipawns": -60,
              "is_mate": false,
              "mate_in": null,
              "comparison_cp": -60
            },
            "loss_cp": 29,
            "within_100cp": true,
            "within_200cp": true,
            "pv": {
              "uci": [
                "e7c5"
              ],
              "san": "16...Bc5"
            },
            "nodes": 250396,
            "depth": 14,
            "seldepth": 30
          }
        ]
      }
    }
  ],
  "limitations": [
    "The six neural checkpoints are scalar evaluators, not move-policy models or explanation models.",
    "Their 768 inputs encode piece placement only; side to move is applied after inference, while castling rights, en-passant state, repetition, move history, and clocks are not model inputs.",
    "Profile labels describe intended training or runtime behavior and do not prove human-like personality or internal understanding.",
    "Stockfish results use a fixed node budget and configuration and are a verification snapshot, not a claim of perfect play.",
    "Stockfish was required to use two search threads. Parallel search can produce small score, depth, node-count, or PV differences on a fresh rerun even when the configured node limit is unchanged.",
    "Centipawn loss uses a 100,000 cp comparison value for forced-mate scores; mate status and mate distance are also reported separately.",
    "The analysis does not measure Elo, playing strength, or clean unseen test accuracy.",
    "Any reader-facing move explanation must describe observable chess features; it must not be presented as the model's internal reasoning."
  ]
}