Fix Scala 3 publishing collision and restore 3.4.1 default

[jonathanvdc]

Scala 3.4.1 and 3.6.4 published to the same _3 artifact coordinates, so sbt +publish uploaded 3.4.1 successfully and then failed with HTTP 409 when publishing 3.6.4.

These changes restore 3.4.1 as the development/IDE default and the Scala 3 publishing baseline, preserving compatibility with older consumers. Keep 3.6.4 in cross-version testing, but skip publishing Scala 3 versions other than the baseline.

[github-actions]

JMH comparison (baseline vs PR)

Benchmark	Params	Baseline	PR	Δ (PR/Base)	Unit
IncrementalBenchmarks.incrementalPolynomial	depth=6, mutableEGraph=false, size=500, threadCount=1	199.163	201.206	1.010× (+1.0%)	ms/op
IncrementalBenchmarks.incrementalPolynomial	depth=6, mutableEGraph=false, size=500, threadCount=2	337.581	335.177	0.993× (-0.7%)	ms/op
IncrementalBenchmarks.incrementalPolynomial	depth=6, mutableEGraph=true, size=500, threadCount=1	8.22359	8.14716	0.991× (-0.9%)	ms/op
IncrementalBenchmarks.incrementalPolynomial	depth=6, mutableEGraph=true, size=500, threadCount=2	90.3973	89.524	0.990× (-1.0%)	ms/op
IncrementalBenchmarks.oneByOnePolynomial	depth=6, mutableEGraph=false, size=500, threadCount=1	332.939	328.594	0.987× (-1.3%)	ms/op
IncrementalBenchmarks.oneByOnePolynomial	depth=6, mutableEGraph=false, size=500, threadCount=2	551.118	555.8	1.008× (+0.8%)	ms/op
IncrementalBenchmarks.oneByOnePolynomial	depth=6, mutableEGraph=true, size=500, threadCount=1	140.287	140.935	1.005× (+0.5%)	ms/op
IncrementalBenchmarks.oneByOnePolynomial	depth=6, mutableEGraph=true, size=500, threadCount=2	334.235	337.367	1.009× (+0.9%)	ms/op
LiarBenchmarks.findGemmInMm	threadCount=1	228.827	228.524	0.999× (-0.1%)	ms/op
LiarBenchmarks.findGemmInMm	threadCount=2	179.064	184.961	1.033× (+3.3%)	ms/op
LiarBenchmarks.findGemvInMv	threadCount=1	63.365	62.9553	0.994× (-0.6%)	ms/op
LiarBenchmarks.findGemvInMv	threadCount=2	57.1268	57.7236	1.010× (+1.0%)	ms/op
MatmulBenchmarks.nmm	mutableEGraph=false, size=20, threadCount=1	4.40994	4.70041	1.066× (+6.6%)	ms/op
MatmulBenchmarks.nmm	mutableEGraph=false, size=20, threadCount=2	4.56257	4.46459	0.979× (-2.1%)	ms/op
MatmulBenchmarks.nmm	mutableEGraph=false, size=40, threadCount=1	30.5798	30.4836	0.997× (-0.3%)	ms/op
MatmulBenchmarks.nmm	mutableEGraph=false, size=40, threadCount=2	23.7025	23.9435	1.010× (+1.0%)	ms/op
MatmulBenchmarks.nmm	mutableEGraph=false, size=80, threadCount=1	248.311	242.551	0.977× (-2.3%)	ms/op
MatmulBenchmarks.nmm	mutableEGraph=false, size=80, threadCount=2	162.588	165.489	1.018× (+1.8%)	ms/op
MatmulBenchmarks.nmm	mutableEGraph=true, size=20, threadCount=1	2.81769	2.83533	1.006× (+0.6%)	ms/op
MatmulBenchmarks.nmm	mutableEGraph=true, size=20, threadCount=2	2.76959	2.93176	1.059× (+5.9%)	ms/op
MatmulBenchmarks.nmm	mutableEGraph=true, size=40, threadCount=1	20.3272	21.0788	1.037× (+3.7%)	ms/op
MatmulBenchmarks.nmm	mutableEGraph=true, size=40, threadCount=2	15.444	15.4436	1.000× (-0.0%)	ms/op
MatmulBenchmarks.nmm	mutableEGraph=true, size=80, threadCount=1	172.651	170.736	0.989× (-1.1%)	ms/op
MatmulBenchmarks.nmm	mutableEGraph=true, size=80, threadCount=2	108.722	107.816	0.992× (-0.8%)	ms/op
PolyBenchmarks.polynomial	mutableEGraph=false, size=5, threadCount=1	87.8738	88.0695	1.002× (+0.2%)	ms/op
PolyBenchmarks.polynomial	mutableEGraph=false, size=5, threadCount=2	81.2708	81.7311	1.006× (+0.6%)	ms/op
PolyBenchmarks.polynomial	mutableEGraph=false, size=6, threadCount=1	412.649	407.623	0.988× (-1.2%)	ms/op
PolyBenchmarks.polynomial	mutableEGraph=false, size=6, threadCount=2	369.018	366.556	0.993× (-0.7%)	ms/op
PolyBenchmarks.polynomial	mutableEGraph=true, size=5, threadCount=1	34.1117	34.0229	0.997× (-0.3%)	ms/op
PolyBenchmarks.polynomial	mutableEGraph=true, size=5, threadCount=2	29.3117	28.7387	0.980× (-2.0%)	ms/op
PolyBenchmarks.polynomial	mutableEGraph=true, size=6, threadCount=1	143.937	143.282	0.995× (-0.5%)	ms/op
PolyBenchmarks.polynomial	mutableEGraph=true, size=6, threadCount=2	117.303	116.486	0.993× (-0.7%)	ms/op
VectorBenchmarks.blinnPhong	mutableEGraph=false, threadCount=1	33684.2	34503.6	1.024× (+2.4%)	ms/op
VectorBenchmarks.blinnPhong	mutableEGraph=false, threadCount=2	32496.5	32563.3	1.002× (+0.2%)	ms/op
VectorBenchmarks.blinnPhong	mutableEGraph=true, threadCount=1	4620.67	4576.7	0.990× (-1.0%)	ms/op
VectorBenchmarks.blinnPhong	mutableEGraph=true, threadCount=2	3194.65	3219.93	1.008× (+0.8%)	ms/op
VectorBenchmarks.gramSchmidt	mutableEGraph=false, threadCount=1	494.419	480.295	0.971× (-2.9%)	ms/op
VectorBenchmarks.gramSchmidt	mutableEGraph=false, threadCount=2	393.069	390.754	0.994× (-0.6%)	ms/op
VectorBenchmarks.gramSchmidt	mutableEGraph=true, threadCount=1	184.213	172.837	0.938× (-6.2%)	ms/op
VectorBenchmarks.gramSchmidt	mutableEGraph=true, threadCount=2	131.434	126.926	0.966× (-3.4%)	ms/op
VectorBenchmarks.reflection	mutableEGraph=false, threadCount=1	299.674	297.026	0.991× (-0.9%)	ms/op
VectorBenchmarks.reflection	mutableEGraph=false, threadCount=2	245.877	241.679	0.983× (-1.7%)	ms/op
VectorBenchmarks.reflection	mutableEGraph=true, threadCount=1	117.897	118.76	1.007× (+0.7%)	ms/op
VectorBenchmarks.reflection	mutableEGraph=true, threadCount=2	85.6461	84.5822	0.988× (-1.2%)	ms/op
VectorBenchmarks.vectorNormalization	mutableEGraph=false, threadCount=1	3.75438	3.76691	1.003× (+0.3%)	ms/op
VectorBenchmarks.vectorNormalization	mutableEGraph=false, threadCount=2	4.3248	4.51208	1.043× (+4.3%)	ms/op
VectorBenchmarks.vectorNormalization	mutableEGraph=true, threadCount=1	1.66551	1.67611	1.006× (+0.6%)	ms/op
VectorBenchmarks.vectorNormalization	mutableEGraph=true, threadCount=2	2.42555	2.45402	1.012× (+1.2%)	ms/op
Geomean	threadCount=1, mutableEGraph=false	—	—	1.000× (+0.0%)
Geomean	threadCount=1, mutableEGraph=true	—	—	0.996× (-0.4%)
Geomean	threadCount=2, mutableEGraph=false	—	—	1.005× (+0.5%)
Geomean	threadCount=2, mutableEGraph=true	—	—	0.999× (-0.1%)

Note: < 1.0× means faster on PR; > 1.0× means slower.