diff --git a/src/game/engine/scenes/tests/auto_play.gd b/src/game/engine/scenes/tests/auto_play.gd
index 98887cad..94d06bce 100644
--- a/src/game/engine/scenes/tests/auto_play.gd
+++ b/src/game/engine/scenes/tests/auto_play.gd
@@ -20,6 +20,9 @@ const ImprovementManagerScript = preload(
 const HappinessScript = preload("res://engine/src/modules/empire/happiness.gd")
 const ItemSystemScript = preload("res://engine/src/modules/management/item_system.gd")
 const SaveManagerScript = preload("res://engine/src/core/save_manager.gd")
+const TurnProcessorHelpersScript = preload(
+	"res://engine/src/modules/management/turn_processor_helpers.gd"
+)
 
 var _improvement_manager: RefCounted = null
 
@@ -1247,15 +1250,12 @@ func _play_turn() -> void:
 
 
 func _pick_research(player: RefCounted) -> void:
-	## p2-43a-followup (5th bullet) / p0-26: scoring logic lives in
-	## `mc-ai::evaluator::ScoringEvaluator::pick_tech`; this call site is a
-	## thin Rail-1 bridge delegation through the shared `GdAiController`
-	## instance held on `GameState`.
-	##
-	## Prereq + already-researched filtering is done in GDScript (cheap, needs
-	## live `player.has_tech` access); the Rust scorer receives a pre-filtered
-	## `AiTechCandidate` list plus the clan's raw 1..=10 axes and picks the
-	## highest-scoring tech.
+	## Rail-1: research selection is scored in
+	## `mc-ai::ScoringEvaluator::pick_tech` and dispatched through the shared
+	## `GdAiController` bridge via `TurnProcessorHelpersScript`. GDScript only
+	## assembles the candidate JSON, reads the clan axes, gathers the p1-29
+	## catch-up observation, and applies the returned tech id — no scoring logic
+	## lives here (single source shared with `turn_processor.gd`).
 	var ctrl: RefCounted = GameState.get_ai_controller()
 	if ctrl == null:
 		push_warning(
@@ -1263,51 +1263,7 @@ func _pick_research(player: RefCounted) -> void:
 			+ "(player will retry next turn)"
 		)
 		return
-
-	# Build prereq-filtered `AiTechCandidate` list. The Rust struct fields:
-	#   {id, pillar, cost, tier, unlocks_buildings, unlocks_units}
-	var candidates: Array = []
-	for tech: Dictionary in DataLoader.get_all_techs():
-		var tid: String = str(tech.get("id", ""))
-		if tid.is_empty() or player.has_tech(tid):
-			continue
-		var met: bool = true
-		for req: Variant in tech.get("requires", []):
-			if not player.has_tech(str(req)):
-				met = false
-				break
-		if not met:
-			continue
-		var unlocks: Dictionary = tech.get("unlocks", {})
-		var unlock_buildings: Array = []
-		for bid: Variant in unlocks.get("buildings", []):
-			unlock_buildings.append(str(bid))
-		var unlock_units: Array = []
-		for uid: Variant in unlocks.get("units", []):
-			unlock_units.append(str(uid))
-		candidates.append({
-			"id": tid,
-			"pillar": str(tech.get("pillar", "")),
-			"cost": maxi(int(tech.get("cost", 1)), 1),
-			"tier": int(tech.get("tier", 0)),
-			"unlocks_buildings": unlock_buildings,
-			"unlocks_units": unlock_units,
-		})
-	if candidates.is_empty():
-		return
-
-	# Personality axes (raw 1..=10) — bridge normalises internally.
-	var clan_id: String = str(player.get("clan_id") if player.get("clan_id") != null else "")
-	var axes: Dictionary = {}
-	if not clan_id.is_empty():
-		var personality: Dictionary = DataLoader.get_ai_personality(clan_id)
-		if personality != null and not personality.is_empty():
-			axes = personality.get("strategic_axes", {})
-
-	var best_id: String = ctrl.pick_research(
-		JSON.stringify(candidates), JSON.stringify(axes)
-	)
-
+	var best_id: String = TurnProcessorHelpersScript.pick_research_via_bridge(ctrl, player)
 	if not best_id.is_empty():
 		player.researching = best_id
 		player.research_progress = 0
diff --git a/src/game/engine/src/entities/auto_play.gd b/src/game/engine/src/entities/auto_play.gd
index 85970554..55ffb652 100644
--- a/src/game/engine/src/entities/auto_play.gd
+++ b/src/game/engine/src/entities/auto_play.gd
@@ -12,6 +12,9 @@ extends Node
 ##     saves/turn_NNNN.save — full GameState.serialize() per turn
 
 const HexUtilsScript = preload("res://engine/src/map/hex_utils.gd")
+const TurnProcessorHelpersScript = preload(
+	"res://engine/src/modules/management/turn_processor_helpers.gd"
+)
 const PathfinderScript = preload("res://engine/src/map/pathfinder.gd")
 const BuildableHelperScript = preload("res://engine/scenes/city/city_buildable_helper.gd")
 const ImprovementManagerScript = preload(
@@ -1214,129 +1217,20 @@ func _play_turn() -> void:
 
 
 func _pick_research(player: RefCounted) -> void:
-	## Score available techs: base = 1000/cost; per-pillar personality multiplier;
-	## unlocks tier≥4 unit adds ×3; prerequisite of high-value tech adds ×1.5.
-	## Personality axes drive per-pillar multipliers so clan research orders diverge:
-	##   military    → aggression (blackhammer rushes military techs)
-	##   metallurgy  → production (ironhold/deepforge prioritise smithing)
-	##   agriculture → expansion (blackhammer/runesmith expand aggressively)
-	##   civics      → wealth + trade_willingness (goldvein)
-	##   scholarship → wealth + production blend (goldvein science income)
-	##   ecology     → expansion × 0.5 + production × 0.5 (deepforge tall-empire)
-	##
-	## Research scoring belongs in mc-ai::ScoringEvaluator::pick_tech (Rail-1).
-	## This test-harness path reads axes inline; wiring through GdAiController
-	## requires the tactical bridge to emit research actions (tracked in p0-26).
-	var all_techs: Array = DataLoader.get_all_techs()
-
-	# Load clan personality axes (1..=10). Defaults to 5 (neutral) if clan
-	# is unset so vanilla scoring degrades gracefully to neutral multipliers.
-	var clan_id: String = str(player.get("clan_id") if player.get("clan_id") != null else "")
-	var axes: Dictionary = {}
-	if not clan_id.is_empty():
-		var personality: Dictionary = DataLoader.get_ai_personality(clan_id)
-		if personality != null and not personality.is_empty():
-			axes = personality.get("strategic_axes", {})
-
-	# Normalise raw 1..=10 axis values to [0, 1] (neutral 5 → 0.44).
-	var agg: float  = _norm_axis(axes, "aggression")
-	var prod: float = _norm_axis(axes, "production")
-	var wlth: float = _norm_axis(axes, "wealth")
-	var trd: float  = _norm_axis(axes, "trade_willingness")
-	var exp: float  = _norm_axis(axes, "expansion")
-
-	# Per-pillar multiplier derived from clan axes (range 1.0..=2.0).
-	# Base of 1.0 ensures clans with low axes still research every pillar.
-	var pillar_mult: Dictionary = {
-		"military":    1.0 + agg,
-		"metallurgy":  1.0 + prod,
-		"agriculture": 1.0 + exp * 0.8,
-		"civics":      1.0 + (wlth + trd) / 2.0 * 0.7,
-		"scholarship": 1.0 + (wlth + prod) / 2.0 * 0.6,
-		"ecology":     1.0 + (exp + prod) / 2.0 * 0.5,
-	}
-
-	# p1-29 cycle 3: catch-up dynamics. Compare this player's tech_era ceiling
-	# against the highest opponent's; when behind by ≥2 eras, boost military +
-	# metallurgy pillars 1.5× and waive the tier-3 mercantile penalty so the
-	# losing player prioritises closing the tech gap rather than minting more
-	# era-1 economy techs (the failure mode in the lever-3+4 batch where p1
-	# stayed at tier_peak=1 forever, never developing).
-	var self_tier_peak: int = _player_tier_peak(player)
-	var opp_tier_peak: int = _max_opponent_tier_peak(player)
-	var is_behind: bool = (opp_tier_peak >= self_tier_peak + 2)
-	# p1-29a cycle 6 isolation flag: `MC_DISABLE_CATCHUP_RESEARCH=1` forces
-	# is_behind to false here (matching the turn_processor.gd::_catchup_research_mult
-	# kill switch). Used by the combat-only batch to attribute which intervention
-	# moves tier_peak_gap.
-	if OS.has_environment("MC_DISABLE_CATCHUP_RESEARCH") \
-			and OS.get_environment("MC_DISABLE_CATCHUP_RESEARCH") == "1":
-		is_behind = false
-	if is_behind:
-		pillar_mult["military"]   = float(pillar_mult["military"])   * 1.5
-		pillar_mult["metallurgy"] = float(pillar_mult["metallurgy"]) * 1.5
-
-	# Pass 1: compute raw score for every tech (ignoring availability).
-	var raw_score: Dictionary = {}
-	for tech: Dictionary in all_techs:
-		var tid: String = str(tech.get("id", ""))
-		if tid.is_empty():
-			continue
-		var cost: int = maxi(int(tech.get("cost", 1)), 1)
-		var sc: float = 1000.0 / float(cost)
-		# Apply personality-driven pillar multiplier (replaces hardcoded x2 for military).
-		var pillar: String = str(tech.get("pillar", ""))
-		sc *= float(pillar_mult.get(pillar, 1.0))
-		# Tier-3+ penalty for mercantile clans (low aggression AND low production).
-		# Guards goldvein/runesmith from racing to tier_peak=6 identically to
-		# ironhold/blackhammer. agg < 0.5 catches raw ≤5; prod < 0.5 catches raw ≤5.
-		# p1-29 cycle 3: waive the penalty when this player is behind on tech —
-		# a losing mercantile player needs to catch up rather than be further
-		# slowed by their personality bias.
-		if int(tech.get("tier", 0)) >= 3 and agg < 0.5 and prod < 0.5 and not is_behind:
-			var trade_factor: float = (wlth + trd) / 2.0  # mercantile bias, [0, 1]
-			sc *= maxf(0.4, 1.0 - trade_factor * 0.6)  # up to 60% penalty for full mercantile clans
-		for uid: Variant in tech.get("unlocks", {}).get("units", []):
-			var udata: Dictionary = DataLoader.get_unit(str(uid))
-			if int(udata.get("tier", 1)) >= 4:
-				sc *= 3.0
-				break
-		raw_score[tid] = sc
-
-	# Pass 2: prerequisites of any tech scoring >= 20 get a 1.5x boost.
-	var prereq_mult: Dictionary = {}
-	for tech: Dictionary in all_techs:
-		var tid: String = str(tech.get("id", ""))
-		if not raw_score.has(tid) or float(raw_score[tid]) < 20.0:
-			continue
-		for req: Variant in tech.get("requires", []):
-			var rid: String = str(req)
-			prereq_mult[rid] = maxf(float(prereq_mult.get(rid, 1.0)), 1.5)
-
-	# Pass 3: pick the highest-scoring available tech.
-	var best_id: String = ""
-	var best_score: float = -1.0
-	for tech: Dictionary in all_techs:
-		var tid: String = str(tech.get("id", ""))
-		if tid.is_empty() or player.has_tech(tid):
-			continue
-		var reqs: Array = tech.get("requires", [])
-		var met: bool = true
-		for req: Variant in reqs:
-			if not player.has_tech(str(req)):
-				met = false
-				break
-		if not met:
-			continue
-		var score: float = float(raw_score.get(tid, 1.0)) * float(prereq_mult.get(tid, 1.0))
-		if score > best_score:
-			best_score = score
-			best_id = tid
+	## Rail-1: research selection is scored in mc-ai::ScoringEvaluator::pick_tech
+	## (the port of this function) and dispatched through the shared
+	## `GdAiController` bridge. GDScript only assembles the candidate JSON, reads
+	## the clan axes, gathers the p1-29 catch-up observation, and applies the
+	## returned tech id — no scoring logic lives here.
+	var ctrl: RefCounted = GameState.get_ai_controller()
+	if ctrl == null:
+		return
+	var best_id: String = TurnProcessorHelpersScript.pick_research_via_bridge(ctrl, player)
 	if not best_id.is_empty():
 		player.researching = best_id
 		player.research_progress = 0
 		if _turn_count <= 5 or _turn_count % 20 == 0:
-			print("  Researching: %s (score %.1f)" % [best_id, best_score])
+			print("  Researching: %s" % best_id)
 
 
 static func _norm_axis(axes: Dictionary, key: String) -> float:
@@ -1347,46 +1241,6 @@ static func _norm_axis(axes: Dictionary, key: String) -> float:
 	return (clampf(raw, 1.0, 10.0) - 1.0) / 9.0
 
 
-static func _player_tier_peak(player: RefCounted) -> int:
-	## Compute the highest tech-era this player has researched. Mirrors the
-	## per-player tier_peak metric written into turn_stats.jsonl. Used by
-	## _pick_research's catch-up branch (p1-29 cycle 3) to detect when this
-	## player is falling behind on the tech ladder.
-	if player == null:
-		return 0
-	var techs: Array = player.researched_techs if player.get("researched_techs") != null else []
-	var peak: int = 0
-	for tid: Variant in techs:
-		var data: Dictionary = DataLoader.get_tech(str(tid))
-		var era: int = int(data.get("era", 0))
-		if era > peak:
-			peak = era
-	return peak
-
-
-static func _max_opponent_tier_peak(self_player: RefCounted) -> int:
-	## Compute the highest opponent's tier_peak across all OTHER players in
-	## GameState.players. Used by _pick_research's catch-up branch.
-	## Returns 0 when self is the only player or no opponents have researched
-	## anything yet (degenerate first-turn case).
-	var max_peak: int = 0
-	if GameState == null or GameState.players == null:
-		return 0
-	var self_idx: int = -1
-	if self_player != null and self_player.get("index") != null:
-		self_idx = int(self_player.index)
-	for p: Variant in GameState.players:
-		if p == null:
-			continue
-		var pi: int = int(p.index) if p.get("index") != null else -1
-		if pi == self_idx:
-			continue
-		var peak: int = _player_tier_peak(p)
-		if peak > max_peak:
-			max_peak = peak
-	return max_peak
-
-
 func _score_site(pos: Vector2i, game_map: RefCounted) -> float:
 	## Score a hex as a city site. Food*2 + production*1.5 + resources.
 	var tile: Resource = game_map.get_tile(pos)
diff --git a/src/game/engine/src/modules/management/turn_processor.gd b/src/game/engine/src/modules/management/turn_processor.gd
index d893811b..ba5d1bed 100644
--- a/src/game/engine/src/modules/management/turn_processor.gd
+++ b/src/game/engine/src/modules/management/turn_processor.gd
@@ -143,13 +143,18 @@ func _process_research(player: RefCounted) -> void:  # Player
 	## Auto-pick fallback: when a player has no current research target
 	## (just completed one, or never picked one — the latter case is the
 	## bug we hit on huge-map 5-clan runs where AI players P1-P4 stalled
-	## at techs=1 forever because nothing ever called `_pick_research`
-	## for them; auto_play.gd only picks for its impersonated current
-	## player slot). Re-pick from the bridge using the same scorer the
-	## headless autoplay uses, so AI players progress through eras
+	## at techs=1 forever because nothing ever picked a tech for them;
+	## auto_play.gd only picks for its impersonated current player slot).
+	## Re-pick via the shared Rail-1 bridge helper (the same scorer the
+	## headless autoplay uses), so AI players progress through eras
 	## naturally instead of sitting idle.
 	if player.researching.is_empty():
-		_auto_pick_research(player)
+		var ctrl: RefCounted = GameState.get_ai_controller()
+		if ctrl != null:
+			var picked: String = TurnProcessorHelpersScript.pick_research_via_bridge(ctrl, player)
+			if not picked.is_empty():
+				player.researching = picked
+				player.research_progress = 0
 		if player.researching.is_empty():
 			return
 
@@ -213,62 +218,6 @@ func _process_research(player: RefCounted) -> void:  # Player
 		_check_resource_reveals(completed_tech, player.index)
 
 
-func _auto_pick_research(player: RefCounted) -> void:
-	## Pick a research target for `player` via the Rust bridge scorer.
-	##
-	## Mirrors the candidate-list construction from
-	## `auto_play.gd::_pick_research`. Runs for every player on every turn
-	## that finds `researching` empty — so AI players P1..P4 (which
-	## auto_play does NOT impersonate via `_play_turn`) actually advance
-	## through eras. Without this, only the auto_play-impersonated slot
-	## ever picked a tech and the rest sat at techs=1 forever (huge-map
-	## batch `20260516_212826`).
-	var ctrl: RefCounted = GameState.get_ai_controller()
-	if ctrl == null:
-		return
-	var candidates: Array = []
-	for tech: Dictionary in DataLoader.get_all_techs():
-		var tid: String = str(tech.get("id", ""))
-		if tid.is_empty() or player.has_tech(tid):
-			continue
-		var met: bool = true
-		for req: Variant in tech.get("requires", []):
-			if not player.has_tech(str(req)):
-				met = false
-				break
-		if not met:
-			continue
-		var unlocks: Dictionary = tech.get("unlocks", {})
-		var unlock_buildings: Array = []
-		for bid: Variant in unlocks.get("buildings", []):
-			unlock_buildings.append(str(bid))
-		var unlock_units: Array = []
-		for uid: Variant in unlocks.get("units", []):
-			unlock_units.append(str(uid))
-		candidates.append({
-			"id": tid,
-			"pillar": str(tech.get("pillar", "")),
-			"cost": maxi(int(tech.get("cost", 1)), 1),
-			"tier": int(tech.get("tier", 0)),
-			"unlocks_buildings": unlock_buildings,
-			"unlocks_units": unlock_units,
-		})
-	if candidates.is_empty():
-		return
-	var clan_id: String = str(player.get("clan_id") if player.get("clan_id") != null else "")
-	var axes: Dictionary = {}
-	if not clan_id.is_empty():
-		var personality: Dictionary = DataLoader.get_ai_personality(clan_id)
-		if personality != null and not personality.is_empty():
-			axes = personality.get("strategic_axes", {})
-	var best_id: String = ctrl.pick_research(
-		JSON.stringify(candidates), JSON.stringify(axes)
-	)
-	if not best_id.is_empty():
-		player.researching = best_id
-		player.research_progress = 0
-
-
 func _check_resource_reveals(completed_tech: String, player_index: int) -> void:
 	TurnProcessorHelpersScript._check_resource_reveals(completed_tech, player_index)
 
diff --git a/src/game/engine/src/modules/management/turn_processor_helpers.gd b/src/game/engine/src/modules/management/turn_processor_helpers.gd
index 4a3fef12..d0b47cab 100644
--- a/src/game/engine/src/modules/management/turn_processor_helpers.gd
+++ b/src/game/engine/src/modules/management/turn_processor_helpers.gd
@@ -269,3 +269,111 @@ static func _get_healing_rate(
 	return 5
 
 
+# ── Research selection (Rail-1: scored in mc-ai, dispatched via GdAiController) ──
+
+
+static func pick_research_via_bridge(ctrl: RefCounted, player: RefCounted) -> String:
+	## Single source of research selection for both the autoplay harness
+	## (`auto_play.gd::_pick_research`) and the per-player auto-pick fallback
+	## (`turn_processor.gd::_process_research`). Assembles the FULL tech list
+	## (Rust runs the prereq-boost + availability passes itself), the clan axes,
+	## and the p1-29 catch-up observation, then delegates scoring to
+	## `mc-ai::ScoringEvaluator::pick_tech` via the bridge. Returns the picked
+	## tech id, or "" when nothing is researchable.
+	if ctrl == null or player == null:
+		return ""
+	var candidates: Array = []
+	for tech: Dictionary in DataLoader.get_all_techs():
+		var tid: String = str(tech.get("id", ""))
+		if tid.is_empty():
+			continue
+		var unlocks: Dictionary = tech.get("unlocks", {})
+		var unlock_buildings: Array = []
+		for bid: Variant in unlocks.get("buildings", []):
+			unlock_buildings.append(str(bid))
+		var unlock_units: Array = []
+		var max_unit_tier: int = 0
+		for uid: Variant in unlocks.get("units", []):
+			unlock_units.append(str(uid))
+			var udata: Dictionary = DataLoader.get_unit(str(uid))
+			max_unit_tier = maxi(max_unit_tier, int(udata.get("tier", 1)))
+		var reqs: Array = []
+		for req: Variant in tech.get("requires", []):
+			reqs.append(str(req))
+		candidates.append({
+			"id": tid,
+			"pillar": str(tech.get("pillar", "")),
+			"cost": maxi(int(tech.get("cost", 1)), 1),
+			"tier": int(tech.get("tier", 0)),
+			"unlocks_buildings": unlock_buildings,
+			"unlocks_units": unlock_units,
+			"requires": reqs,
+			"max_unit_tier": max_unit_tier,
+			"already_researched": bool(player.has_tech(tid)),
+		})
+	if candidates.is_empty():
+		return ""
+	var clan_id: String = str(player.get("clan_id") if player.get("clan_id") != null else "")
+	var axes: Dictionary = {}
+	if not clan_id.is_empty():
+		var personality: Dictionary = DataLoader.get_ai_personality(clan_id)
+		if personality != null and not personality.is_empty():
+			axes = personality.get("strategic_axes", {})
+	var research_behind: bool = _research_behind(player)
+	return str(ctrl.pick_research(
+		JSON.stringify(candidates), JSON.stringify(axes), research_behind
+	))
+
+
+static func _research_behind(player: RefCounted) -> bool:
+	## p1-29 catch-up observation: true when this player's tech-era ceiling is at
+	## least 2 eras below the highest opponent's. The DECISION driven by this flag
+	## (military/metallurgy ×1.5, waive the tier-3 mercantile penalty) lives in
+	## mc-ai::score_tech — only the cross-player observation is gathered here.
+	##
+	## Kill switch (p1-29a cycle 6 isolation batch): `MC_DISABLE_CATCHUP_RESEARCH=1`
+	## forces the flag false, matching the science-yield kill switch in
+	## turn_processor.gd::_catchup_research_mult. Used to attribute which
+	## intervention moves tier_peak_gap.
+	if OS.has_environment("MC_DISABLE_CATCHUP_RESEARCH") \
+			and OS.get_environment("MC_DISABLE_CATCHUP_RESEARCH") == "1":
+		return false
+	return _max_opponent_tier_peak(player) >= _player_tier_peak(player) + 2
+
+
+static func _player_tier_peak(player: RefCounted) -> int:
+	## Highest tech-era this player has researched (mirrors the per-player
+	## tier_peak metric in turn_stats.jsonl).
+	if player == null:
+		return 0
+	var techs: Array = player.researched_techs if player.get("researched_techs") != null else []
+	var peak: int = 0
+	for tid: Variant in techs:
+		var data: Dictionary = DataLoader.get_tech(str(tid))
+		var era: int = int(data.get("era", 0))
+		if era > peak:
+			peak = era
+	return peak
+
+
+static func _max_opponent_tier_peak(self_player: RefCounted) -> int:
+	## Highest opponent tier_peak across all OTHER players in GameState.players.
+	## Returns 0 when self is the only player or no opponents have researched.
+	var max_peak: int = 0
+	if GameState == null or GameState.players == null:
+		return 0
+	var self_idx: int = -1
+	if self_player != null and self_player.get("index") != null:
+		self_idx = int(self_player.index)
+	for p: Variant in GameState.players:
+		if p == null:
+			continue
+		var pi: int = int(p.index) if p.get("index") != null else -1
+		if pi == self_idx:
+			continue
+		var peak: int = _player_tier_peak(p)
+		if peak > max_peak:
+			max_peak = peak
+	return max_peak
+
+