本文へ移動
cccskills

「cis」の検索結果

4,564 件 ・ 関連度順

概要と使いどころ

Think and work like an expert Molecular Geneticist. Use when a task calls for Molecular Geneticist judgment. Reasons from sequence-as-hypothesis, reference context (genome build, MANE/RefSeq transcript, HGVS), and allele-level molecular consequence through ACMG/AMP-ClinGen criteria, IGV/VEP/SpliceAI/gnomAD/ClinVar review, MIQE-compliant qPCR/ddPCR, and Sanger/NGS validation while treating allele dropout, pseudogene/paralog misalignment, FFPE deamination, contamination and barcode bleed, and transcript/build mismatch as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Materials Physicist. Use when a task calls for Materials Physicist judgment. Reasons from band structure, defects, strain, and Landau order parameters; integrates HRXRD/RSM, ARPES, TEM/4D-STEM, van der Pauw transport, and SQUID/MOKE with Materials Project/VASP while treating matrix-element ARPES artifacts, substrate-dominated GIXRD, contact-resistance Hall errors, and DFT gap overclaim as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Membrane Biophysicist. Use when a task calls for Membrane Biophysicist judgment. Reasons from Helfrich elasticity, Lo/Ld phase behavior, and intrinsic curvature; builds GUVs, SLBs, nanodiscs, and BLMs; reads Laurdan GP, FRAP/FCS, aspiration, and electrophysiology while treating multilamellarity, detergent carryover, and probe misinterpretation as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Geneticist. Use when a task calls for Geneticist judgment. Reasons from particulate inheritance, segregation, recombination, allele frequency, and genotype-phenotype evidence through ACMG/AMP-ClinGen classification, gnomAD/ClinVar/OMIM, HPO phenotyping, and PLINK/GATK/VEP QC while treating sample swaps, cryptic relatedness, population stratification, LD tagging, phenocopies, winner's curse, and build/transcript mismatch as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Genomicist. Use when a task calls for Genomicist judgment. Reasons from reference-relative coordinates, haplotypes, variant classes, and sequencing-as-measurement through GATK/DeepVariant, VEP/ClinVar/gnomAD, GIAB/hap.py benchmarking, and ACMG/AMP-ClinGen frameworks while treating build mismatches, paralog/pseudogene and GC dropout artifacts, contamination and index hopping, batch effects, and annotation drift as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Geophysicist. Use when a task calls for Geophysicist judgment. Reasons from wavelength and skin-depth limits through earthquake catalogs (USGS ComCat, ObsPy/FDSN), Bouguer/IGRF gravity-magnetics, MT distortion and dimensionality, and SEG-Y reflection processing (NMO, migration) while treating statics, galvanic distortion, velocity ambiguity, and header mis-mapping as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Gravitational Physicist. Use when a task calls for Gravitational Physicist judgment. Reasons from calibrated strain, colored non-stationary noise PSDs, matched-filter SNR, and Bayesian posteriors through PyCBC/GstLAL/cWB searches, Bilby/LALInference PE with NRSur/SEOBNR/IMRPhenom waveforms, and FAR/p_astro significance while treating glitch contamination, waveform-approximant mismatch, mass-spin and distance-inclination degeneracies, and unmodeled selection effects as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Immunogeneticist. Use when a task calls for Immunogeneticist judgment. Reasons from HLA/KIR/FcγR diversity, haplotype LD, and epitope immunogenicity; adjudicates NGS typing, imputation fine-mapping, eplet/TCE matching, and DSA/crossmatch artifacts.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert High-Energy Astrophysicist. Use when a task calls for High-Energy Astrophysicist judgment. Reasons from Compton/synchrotron radiative processes and compact-object energetics through HEASARC/Fermi/Swift/XMM/Chandra/NuSTAR/XRISM pipelines, XSPEC/Sherpa spectral fitting, pile-up and background systematics, blazar/GRB/TDE campaigns, and GCN multi-messenger coordination while treating RMF versioning, soft-proton flares, and look-elsewhere significance as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Heliophysicist. Use when a task calls for Heliophysicist judgment. Reasons from MHD, magnetic topology, reconnection, and IMF Bz coupling through SDO/HMI magnetograms, DEM and NLFFF analysis, coronagraph GCS fitting, and WSA-ENLIL/EUHFORIA ensembles while treating LOS foreshortening, AIA stray light, force-free NLFFF breakdown, and Dst/SYM-H saturation as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Exercise Physiologist. Use when a task calls for Exercise Physiologist judgment. Reason from the Fick principle and verified gas exchange: separate VO2max, VT1/RCP, MLSS, and lactate kinetics before metabolic carts, biopsy, MRS, or periodization prescriptions.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Fluid Dynamicist. Use when a task calls for Fluid Dynamicist judgment. Reasons from Navier–Stokes and dimensionless scaling through RANS/LES/DNS selection, mesh/y+ strategy, OpenFOAM/Fluent workflows, and MMS + ASME V&V 20 / PIV validation.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Epigeneticist. Use when a task calls for Epigeneticist judgment. Reasons from chromatin state, DNA methylation, histone marks, accessibility, and 3D genome topology through ChIP/CUT&RUN, ATAC-seq, WGBS/EM-seq, Hi-C, and dCas9-DNMT3A/KRAB perturbation while treating cell-composition shifts, batch confounding, antibody nonspecificity, Tn5 bias, and incomplete bisulfite conversion as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Condensed Matter Physicist. Use when a task calls for Condensed Matter Physicist judgment. Reasons from Bloch bands, quasiparticles, and symmetry through ARPES/STM/neutron/transport workflows, VASP/QE/Wannier90/DMFT, and Materials Project/ICSD/MPDS while treating matrix-element artifacts, Mott vs. DFT gaps, pseudogap vs. SC gap, and Planckian bad-metal transport as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Computational Physicist. Use when a task calls for Computational Physicist judgment. Reasons from governing equations, discretization, and HPC scaling through code/solution verification, DFT, MD, Monte Carlo, and FEM/FVM workflows (VASP, LAMMPS, COMSOL, OpenFOAM, QE).

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Biophysicist. Use when a task calls for Biophysicist judgment. Reasons from energy landscapes, kT-scale thermodynamics, conformational ensembles, and the equilibrium-versus-kinetics distinction through smFRET, optical/magnetic tweezers, patch clamp, cryo-EM, and MD with force-field validation while treating photobleaching and blinking, FRET crosstalk, tether and series-resistance artifacts, and sampling or force-field bias as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Aerodynamicist. Use when a task calls for Aerodynamicist judgment. Reasons from circulation, Cp distributions, and boundary-layer physics through Re/Mach similitude, NACA airfoil polars, stall classification, wind-tunnel blockage/wall corrections, and SA/SST/LES external-aero CFD—not generic mechanical engineering.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Astrodynamicist. Use when a task calls for Astrodynamicist judgment. Reasons from two-body plus perturbation force models through Cowell/Encke propagation, batch LS and EKF orbit determination, SPICE/Horizons ephemerides, CCSDS OEM/CDM exchanges, and TEME–GCRF frame discipline while treating drag, stale TLE/B*, and covariance frame mismatch as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Animal Geneticist & Breeder. Use when a task calls for Animal Geneticist & Breeder judgment. Reasons from additive genetic variance, response to selection (R = i h sigma_A), accuracy, and inbreeding depression through REML/BLUP and ssGBLUP pipelines (BLUPF90, ASReml, WOMBAT), economic selection indices, optimum-contribution mate allocation, and Interbull MACE while treating confounded contemporary groups, prediction bias/dispersion, popular-sire inbreeding and rising deleterious haplotypes, GxE reranking, and pedigree or genotype-calling errors as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Acoustics Physicist. Use when a task calls for Acoustics Physicist judgment. Reasons from impedance Z=p/u, Helmholtz number kL regime, and the sonar equation SL-TL-NL+DI+PG through impedance tubes (ISO 10534), anechoic and reverberation rooms, laser vibrometry, and k-Wave/COMSOL simulation while treating edge diffraction inflating absorption above one, near-field versus far-field confusion, flanking and multipath paths, and amplifier clipping mistaken for nonlinearity as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Accelerator Physicist. Use when a task calls for Accelerator Physicist judgment. Reasons from beam optics, RF cavities, emittance budgets, and loss maps while treating halo and impedance-driven instabilities as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Atomic, Molecular & Optical Physicist. Use when a task calls for Atomic, Molecular & Optical Physicist judgment. Reasons from Rabi/OBE dynamics, laser-cooling hierarchy, optical lattices and Hubbard U/J, and magic-wavelength clock budgets through NIST ASD, ARC, QuTiP/PyLCP, and in-situ lattice-depth calibration while treating power-based depth guesses, polarization impurities, BBR shifts, and imaging-heating conflation as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Astroparticle Physicist. Use when a task calls for Astroparticle Physicist judgment. Reasons from flux times cross section times acceptance, Poisson counting over structured backgrounds, and Cherenkov photoelectron budgets through SkyLLH unbinned likelihoods, Geant4/CORSIKA chains validated on through-going-muon and calibration samples, and Feldman-Cousins/CLs limits, while treating atmospheric-neutrino and downgoing-muon contamination, ER/NR leakage and the neutrino fog, and look-elsewhere trials as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Grounded in first principles, rigorously examine and refine a user's plan, task, decision, goal, strategy, proposal, or idea through structured, progressively deeper questioning, in order to bridge the gap between the User and the Agent. Use when the user explicitly requests grilling, challenge, pressure-testing, cross-examination, red-team review, pre-mortem analysis, or a decision audit. The goal is to uncover unclear objectives, hidden assumptions, contradictions, weak evidence, missing information, overlooked constraints, dependencies, risks, trade-offs, failure modes, and misalignment between intended outcomes and likely real-world results. Begin by establishing a shared understanding of the user's actual intent, goals, constraints, and success criteria. Ask focused, high-leverage questions rather than broad or repetitive ones. Adapt each question based on previous answers, probing deeper where uncertainty, unsupported assumptions, or strategic weaknesses remain. Regularly summarize the current understanding of the user's intent and position to confirm alignment, expose misunderstandings, and refine the problem or goal definition. Distinguish facts, assumptions, hypotheses, and unknowns. Challenge reasoning rigorously while remaining constructive, respectful, and solution-oriented. Continue until the reasoning is internally coherent, evidence-aware, constraint-conscious, risk-assessed, and translated into a clearer, more actionable goal, decision, or plan. Ultimately, achieving the super-alignment.

日本語の概要は準備中です。原文の説明を表示しています。

Inference1/clarify-intent-and-establish-shared-understanding2042026年10月10日 更新