本文へ移動
cccskills

K-Dense

@K-Dense-AI

組織

A world leader in empowering scientists with AI agentic tools.

659 スキル8 リポジトリ 5.8万

スキル(659)

検索で絞り込む

Think and work like an expert Environmental Engineer. Use when a task calls for Environmental Engineer judgment. Reasons from mass balances, reaction kinetics, source-pathway-receptor transport, and permit limits through BioWin/GPS-X, SWMM, AERMOD/CALPUFF, GAC/IX and activated-sludge design, and 40 CFR Part 136 QA/QC, while treating nitrifier washout, clarifier upset, PFAS breakthrough, and remediation rebound 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-agents2222026年10月3日 更新

Think and work like an expert Environmental Health Scientist. Use when a task calls for Environmental Health Scientist judgment. Reasons from source–pathway–receptor chains, classical vs Berkson exposure error, and tiered biomonitoring (NHANES/BEs); runs STROBE-grade epi, IRIS/OEHHA/ATSDR risk assessment, AERMOD/CALPUFF, EPHT/EJSCREEN, and HIA while treating surrogate misclassification, mobility bias, and detection≠harm 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-agents2222026年10月3日 更新

Think and work like an expert Epidemiologist. Use when a task calls for Epidemiologist judgment. Reasons from person-time, transmission dynamics, and population case definitions through epidemic curves, DAGs, renewal and SEIR models (EpiEstim, deSolve), SaTScan clustering, and STROBE/ORION/GRADE standards while treating confounding, collider stratification from test-positive conditioning, reporting-delay and testing-intensity artifacts, and superspreading overdispersion 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-agents2222026年10月3日 更新

Think and work like an expert Formal Methods Researcher. Use when a task calls for Formal Methods Researcher judgment. Reasons from operational semantics and temporal logics through SPIN/TLA+/PRISM, Coq/Lean/Isabelle, Z3/CVC5, refinement and separation logic, vacuity and false-positive diagnosis, and Dafny/F* versus property-based testing boundaries.

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-agents2222026年10月3日 更新

Think and work like an expert Experimental Physicist. Use when a task calls for Experimental Physicist judgment. Reasons from GUM error budgets, traceable calibration chains, and multiplied signal-chain transfer functions — separating Type A and Type B uncertainty, null runs, and ELN-linked reproducibility before precision or discovery claims.

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-agents2222026年10月3日 更新

Think and work like an expert Electronic Materials Engineer. Use when a task calls for Electronic Materials Engineer judgment. Reasons from band alignment, defect chemistry, and process–structure–property links; correlates Hall, C–V (Dit), XRD/RSM, SIMS, and ALD/MOCVD/sputtering recipes while treating dopant activation vs. chemical dose, high-κ trap charging, and reliability (NBTI/TDDB) 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-agents2222026年10月3日 更新

Think and work like an expert Environmental Microbiologist. Use when a task calls for Environmental Microbiologist judgment. Reasons from spatial patchiness, redox thermodynamic ceilings, and process-over-taxonomy guild function through DADA2/QIIME2 amplicons keyed to SILVA/GTDB/PR2/UNITE, metaSPAdes/MetaBAT2 MAGs vetted by CheckM/GUNC, and SIP/qSIP rate assays paired with IC/GC/ICP-MS chemistry, while treating extraction-batch effects, relic and extracellular DNA, primer-window bias, and core 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-agents2222026年10月3日 更新

Think and work like an expert Computer Architecture Researcher. Use when a task calls for Computer Architecture Researcher judgment. Reasons from ISA semantics, AMAT/CPI, MESI coherence, and branch prediction through gem5/SPEC/MLPerf evaluation, Amdahl and roofline discipline, TPU/GPU dataflow accelerators, DVFS/EDP, and Spectre/Meltdown mitigation overhead at ISCA/MICRO/HPCA rigor.

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-agents2222026年10月3日 更新

Think and work like an expert Distributed Systems Researcher. Use when a task calls for Distributed Systems Researcher judgment. Reasons from failure models, consistency contracts, and tail-latency-and-recovery performance through TLA+ model checking, Jepsen and Porcupine linearizability checking, and YCSB/DeathStarBench benchmarking with iptables and kill -9 fault injection, while treating unbounded leases and split-brain, clock skew under NTP, and GC-induced p99 spikes 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-agents2222026年10月3日 更新

Think and work like an expert Digital Pathology Scientist. Use when a task calls for Digital Pathology Scientist judgment. Reasons from whole-slide pixels, pathologist-ground-truth label levels, and stain/scanner batch effects through QuPath, CLAM/TIAToolbox MIL, Macenko/Vahadane normalization, and MI-CLAIM/TRIPOD+AI standards while treating patch-level leakage, scanner-ID shortcuts, attention-on-necrosis artifacts, and inter-pathologist-kappa ceilings 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-agents2222026年10月3日 更新

Think and work like an expert Corrosion Engineer. Use when a task calls for Corrosion Engineer judgment. Reasons from electrochemical couples, Pourbaix/galvanic selection, and ISO 15156 sour-service limits through AMPP SP0169/SP0502 CP and ECDA, CO₂ models (NORSOK M-506, OLI), coupon/ER/LPR monitoring, and ASTM G5/G48/G61 qualification while treating IR-masked CIPS, salt-spray overclaim, MIC vs. biocide residual, and MR0175≠fit-for-service 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-agents2222026年10月3日 更新

Think and work like an expert Computational Social Scientist. Use when a task calls for Computational Social Scientist judgment. Reasons from social mechanisms, measurement validity, and sampling frames through DAGs, fixed-effects and IV/DiD/RDD designs, ERGM/SAOM network models, and human-audited text classifiers while treating unobserved homophily, network interference and SUTVA violations, platform-driven selection, bot contamination, and digital-skew unrepresentativeness 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-agents2222026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-agents2222026年10月3日 更新

Think and work like an expert Computational Neuroscientist. Use when a task calls for Computational Neuroscientist judgment. Reasons from encoding/decoding, GLM/LNP spike-train likelihood, mean-field E-I balance, and neural manifolds through NEST/Brian/NEURON/BMTK, GPFA/LFADS, Brain-Score alignment, and trained-RNN reverse engineering while treating spike-sorting contamination, model non-identifiability, nested-CV leakage, and task-optimization≠mechanism 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-agents2222026年10月3日 更新

Think and work like an expert Computational Linguist. Use when a task calls for Computational Linguist judgment. Reasons from UD/PTB formalisms, validate.py/eval.py (LAS/MLAS/ELAS), and evalb .prm settings through Stanza/UDPipe pipelines, PropBank/FrameNet/AMR/UMR layers, IAA (κ, Krippendorff α), CONDA contamination checks, and ARR reproducibility while treating tokenizer mismatch, oracle inflation, train–test leakage, and guideline 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-agents2222026年10月3日 更新

Think and work like an expert Computational Chemist. Use when a task calls for Computational Chemist judgment. Reasons from Kohn–Sham DFT, def2/D4 functional selection, and conformer ensembles through VASP/Gaussian/ORCA, AMBER/GROMACS MD, CREST/CENSO sampling, ONIOM/QM/MM electrostatic embedding, GMTKN55 validation, and SCF convergence escalation while treating B3LYP/6-31G*, BSSE, link-atom artifacts, and force-field 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-agents2222026年10月3日 更新

Think and work like an expert Composites Engineer. Use when a task calls for Composites Engineer judgment. Reasons from CLT/ABD laminate mechanics, Halpin–Tsai micromechanics, and CMH-17/NCAMP allowables through autoclave/OOA/RTM process control, ASTM D30 mechanical qualification, ultrasonic C-scan and CAI damage tolerance while treating fiber waviness, void content, under-cure, and quasi-isotropic strength 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-agents2222026年10月3日 更新

Think and work like an expert Comparative Physiologist. Use when a task calls for Comparative Physiologist judgment. Reason from the Krogh principle and oxygen cascade through intermittent-flow respirometry, SMR/BMR/MMR scope, Q10 and heterothermy, hemoglobin P50, allometry and PGLS, while treating chamber drift, activity artifacts, phylogenetic pseudoreplication, and SMR definition 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-agents2222026年10月3日 更新

Think and work like an expert Control Systems Engineer. Use when a task calls for Control Systems Engineer judgment. Reasons from plant dynamics, stability margins, and disturbance-rejection specs through Bode/Nyquist and Routh-Hurwitz analysis, LQR/H-infinity and pole placement, Kalman/EKF observers, RGA pairing, and HIL validation while treating integrator windup, actuator saturation and backlash limit cycles, sensor delay masking phase margin, and estimator divergence 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-agents2222026年10月3日 更新

Think and work like an expert Construction Engineer. Use when a task calls for Construction Engineer judgment. Reasons from design intent versus means-and-methods through CPM/P6 and Last Planner scheduling, Revit/Navisworks BIM coordination, IBC Chapter 17 special inspections, ASTM C31/C39 cylinder acceptance, and ACI 318 low-break/core protocols while treating formwork collapse, honeycombing, tolerance stack-up, and schedule logic 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-agents2222026年10月3日 更新

Think and work like an expert Differential Geometer. Use when a task calls for Differential Geometer judgment. Reasons from connections, curvature, and holonomy; fixes Lee vs Besse/MTW Riemann signs; uses SageManifolds/xAct/Cadabra, Chern–Weil and Atiyah–Singer index theory, and model-space checks (S^n, flat tori) while treating chart artifacts, torsion misuse, and CAS convention 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-agents2222026年10月3日 更新

Think and work like an expert Dairy Scientist. Use when a task calls for Dairy Scientist judgment. Reasons from the lactation curve, dry matter intake, and rumen health through NASEM Dairy 2021/CNCPS ration formulation, Penn State particle separation, DHIA records, and pen-level mixed models while treating subacute ruminal acidosis, milk fat depression, transition-cow hypocalcemia, and unadjusted DIM/parity confounding 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-agents2222026年10月3日 更新

Think and work like an expert Data Engineer. Use when a task calls for Data Engineer judgment. Reasons from idempotent ELT, medallion bronze/silver/gold, Kimball grain and SCD2, CDC/Debezium and watermark incremental loads, dbt/GX quality gates, Airflow/Dagster orchestration, Iceberg/Delta lakehouse MERGE, data contracts and freshness SLIs while treating silent join drops, duplicate amplification, schema drift, and green-DAG-wrong-numbers 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-agents2222026年10月3日 更新

Think and work like an expert Data Scientist. Use when a task calls for Data Scientist judgment. Reasons from CRISP-DM business estimands, leakage-safe sklearn Pipelines and nested CV, SQL/warehouse semantic metrics, A/B power and SRM/AA guardrails, causal DAG covariate discipline, and Model Cards/Datasheets while treating train-test leakage, Simpson's paradox, peeking, and PSI>0.25 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-agents2222026年10月3日 更新

あなたのアカウントですか? GitHub 連携でクリエイターページにまとめられます