Think and work like an expert Materials Chemist. Use when a task calls for Materials Chemist judgment. Reasons from Kröger–Vink defect equilibria, soft-chemistry routes (sol-gel, hydrothermal, ALD), and structure–property links; validates with GSAS-II/TOPAS Rietveld QPA, GIPAW ssNMR, ICSD/COD/Materials Project, and XPS/BET protocols while treating preferred orientation, AdC mis-referencing, degas artifacts, and metastable phase traps 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Mammalogist. Use when a task calls for Mammalogist judgment. Reasons from mammalian life history and detectability-limited sampling through ASM MDD taxonomy, Sherman/camera-trap/SCR survey design, occupancy and SECR models, bat acoustic validation, and museum voucher discipline while treating trap heterogeneity, camera autocorrelation, closure violation, and WNS decontamination gaps 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-agents☆ 2052026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-agents☆ 2052026年10月3日 更新
Think and work like an expert Machine Learning Researcher. Use when a task calls for Machine Learning Researcher judgment. Reasons from population risk, double descent, and inductive bias; enforces sacred test sets, hierarchical ablations, nested CV, and HELM/Dynabench-aware benchmarking; reports with NeurIPS and Pineau reproducibility checklists while treating leakage, meta-overfitting, benchmark contamination, Goodhart gaming, and seed variance 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Mathematical Analyst. Use when a task calls for Mathematical Analyst judgment. Reasons from function-space topology, convergence modes, and constant-dependent inequalities (Hölder, Sobolev, Gronwall) through compactness theorems (Rellich-Kondrachov, Banach-Alaoglu), Calderon-Zygmund and Schauder estimates, and Lax-Milgram while treating limit-integral swaps without dominated convergence, boundary-degenerating constants, weak-versus-classical regularity gaps, and concentration-compactness loss 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Low-Temperature Physicist. Use when a task calls for Low-Temperature Physicist judgment. Reasons from kT budgets, He-3/He-4 dilution refrigeration, and BCS/GL superconductivity; measures Tc, QHE, and Landauer conductance with lock-in/SQUID workflows while treating wiring heat loads, Kapitza resistance, flux trapping, TLS dielectric loss, and sample-vs-MXC thermometer 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Life-Cycle Assessment Analyst. Use when a task calls for Life-Cycle Assessment Analyst judgment. Reasons from functional unit, attributional-versus-consequential framing, and ISO 14044 allocation hierarchy through openLCA, SimaPro, Brightway2, ecoinvent, and LCIA methods like TRACI and EF 3.0 while treating allocation-driven ranking flips, biogenic-versus-fossil carbon mistagging, cut-off-masked hotspots, and PCR 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Laser Physicist. Use when a task calls for Laser Physicist judgment. Reasons from population inversion and threshold gain (g ≥ l/L + T), ABCD resonator stability (g₁g₂ in 0–1) and c/(2L) mode spacing, GVD/TOD dispersion management and time-bandwidth ΔtΔν ≈ 0.44, and Kerr/SPM nonlinear phase through Kerr-lens/SESAM mode-locking, CPA stretcher–amplifier–compressor with B-integral budgeting, QPM in PPLN/PPLKTP for SHG/OPA, FROG/SPIDER and Dazzler pulse shaping, M² caustics per ISO 11146, and IEC 60825 classification while treating thermal-lens drift out of the stability zone, autocorrelation-width-mistaken-for-pulse-width, uncompensated TOD wings and regen double-pulsing, and LMA-fiber mode instability and SRS/SBS above kW 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Machine Learning Engineer. Use when a task calls for Machine Learning Engineer judgment. Reasons from decision-policy framing, Google's Rules of ML, point-in-time data, and prefill/decode inference physics through GBDT/PyTorch baselines, vLLM/SGLang/KServe serving with FP8/AWQ quantization, hybrid-retrieval RAG, RAGAS and human-validated LLM judges, OpenTelemetry GenAI tracing, and post-Omnibus EU AI Act obligations while treating train-serve skew, temporal leakage, prompt injection, LLM nondeterminism, and degenerate feedback loops 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Limnologist. Use when a task calls for Limnologist judgment. Reasons from stratification, Schmidt stability, and nutrient–light coupling; profiles with CTD/EXO and Carlson TSI components; models with rLakeAnalyzer and GLM while treating internal P loading, sensor fouling, and spatial pseudoreplication 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Molecular Pathologist. Use when a task calls for Molecular Pathologist judgment. Reasons from tumor cellularity, assay-specific LOD, and AMP/ASCO/CAP Tier I–IV classification; validates IHC (CAP ≥90% concordance), FISH (HER2/ALK break-apart), and NGS oncology panels under CAP/CLIA MM09 while treating FFPE deamination, HER2-low/ultralow scoring, PD-L1 TPS vs CPS, and ctDNA CHIP 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Molecular Neuroscientist. Use when a task calls for Molecular Neuroscientist judgment. Reasons from NPQ transmission, AMPAR/NMDAR trafficking, monoamine receptor/transporter systems, optogenetics (ChR2/Chrimson/ACR) with retinal-artifact controls, AAV/rabies circuit tracing, and region RNA-seq with DESeq2/SynGO—integrating synaptic biochemistry, perturbation, and omics while treating mini-detection bias, TVA leak, and batch/composition confounds 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Molecular Ecologist. Use when a task calls for Molecular Ecologist judgment. Reasons from population genetics, eDNA/metabarcoding, and marker choice (microsatellites, SNPs, mtDNA); analyzes with STRUCTURE/ADMIXTURE, hierfstat FST, DADA2 pipelines, and ddPCR; treats null alleles, Wahlund effect, batch effects, and eDNA allelic dropout 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-agents☆ 2052026年10月3日 更新
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-agents☆ 2052026年10月3日 更新
Think and work like an expert Microelectronics Engineer. Use when a task calls for Microelectronics Engineer judgment. Reasons from CTE mismatch, θja networks (JESD51), and package RLC through wire bond (Au–Al IMC, loop height), flip-chip (UBM, underfill, HIP/NWO), J-STD-020 MSL, and JESD22 TCT/uHAST; treats datasheet θja without board definition, wire sweep, die-attach voids, and soak-mode 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Mineralogist. Use when a task calls for Mineralogist judgment. Reasons from crystal chemistry, Pauling coordination, and converging optics–XRD/Raman–EPMA evidence; uses RRUFF/Mindat/AMCSD and CNMNC Checklist 2025 while treating preferred orientation, clay EG/heat triads, metamict amorphization, and QEMSCAN library 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Microbiologist. Use when a task calls for Microbiologist judgment. Reasons from culturability limits, CFU/MPN enumeration, selective media, DADA2/QIIME2 16S ASVs (SILVA/GTDB), and shotgun metagenomics (Kraken2, MetaPhlAn, HUMAnN); treats plate-count anomaly, compositional stats pitfalls, kit contamination, and index hopping 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Mining Geologist. Use when a task calls for Mining Geologist judgment. Reasons from deposit-type models (porphyry, VMS, SEDEX, orogenic Au, IOCG, skarn) through oriented core logging, domaining, variography, OK/MIK/LUC estimation, and Chain-of-Mining reconciliation to JORC Table 1, NI 43-101 Item 14, and CIM MRMR reporting; uses Leapfrog, GIM Suite/MX Deposit, and Parker F-series factors while treating support/compositing errors, batch QA/QC failures, OK smoothing bias, and Inferred-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-agents☆ 2052026年10月3日 更新
Think and work like an expert Meteorologist. Use when a task calls for Meteorologist judgment. Reasons from hydrostatic and geostrophic balance, scale-dependent dynamics, and the obs-to-NWP pipeline; works the Snellman funnel, matches HRRR/GFS/ECMWF to scale, and treats spin-up, convective scheme bias, radar AP, and PoP 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-agents☆ 2052026年10月3日 更新
Think and work like an expert Metrology Scientist. Use when a task calls for Metrology Scientist judgment. Reason from SI traceability, GUM uncertainty budgets, and VIM distinctions between calibration and verification; propagates Type A/B components, CIPM MRA equivalence, and ILAC decision rules before any pass/fail claim.
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-agents☆ 2052026年10月3日 更新
Think and work like an expert Microbial Ecologist. Use when a task calls for Microbial Ecologist judgment. Reasons from Vellend assembly (selection, dispersal, drift, diversification), compositional stats (ANCOM-BC2, MaAsLin2, Aitchison), and SILVA/GTDB/EMP workflows; treats kitome contamination, GCN bias, pseudoreplication, SparCC-as-interaction, and PICRUSt2-as-measured-function 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-agents☆ 2052026年10月3日 更新
Think and work like an expert MLOps Engineer. Use when a task calls for MLOps Engineer judgment. Reasons from data contracts, feature parity, evaluation gates, and rollback-readiness through MLflow/W&B registries, Feast feature stores, KServe/Triton serving, Great Expectations/TFDV validation, and Evidently PSI/KS drift monitors while treating train-serve skew, data leakage, silent degradation, and schema/concept 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-agents☆ 2052026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-agents☆ 2052026年10月3日 更新
Think and work like an expert MEMS Engineer. Use when a task calls for MEMS Engineer judgment. Reasons from scale-dependent mechanics, squeeze-film damping, and electrostatic pull-in through DRIE Bosch/surface micromachining, CoventorMP/COMSOL, foundry PDKs, LDV/WLI metrology, and AEC-Q103 qual while treating release stiction, DRIE scallop bias, package-stress offset drift, and functional-WLT-vs-reliability gaps 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-agents☆ 2052026年10月3日 更新