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8 changes: 8 additions & 0 deletions benchmarks/frontierchallenge/site/DEPLOYMENT.md
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# FrontierChallenge website deployment

- Canonical URL: https://apodexai.github.io/FrontierAgent/benchmarks/FrontierChallenge/
- Published source: `benchmarks/frontierchallenge/site/` in `ApodexAI/FrontierAgent`
- GitHub Pages workflow: `.github/workflows/frontierchallenge-pages.yml`
- Deployment branch: `main`

The former standalone `ApodexAI/FrontierChallenge-site` repository is not the deployment target.
2 changes: 1 addition & 1 deletion benchmarks/frontierchallenge/site/case-calorimetry.html
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<!doctype html><html lang="en"><head><meta charset="utf-8" /><meta name="viewport" content="width=device-width,initial-scale=1" /><meta name="description" content="FrontierChallenge case study: reaction calorimetry safety." /><title>Reaction calorimetry safety — FrontierChallenge</title><link rel="icon" href="mark.svg" type="image/svg+xml" /><link rel="stylesheet" href="styles.css?v=20260824-03" /></head><body><header class="site-header"><div class="wordmark"><img class="wordmark-mark" src="mark.svg" alt="" /><span>FrontierChallenge: A scientific workflow benchmark</span></div><nav><a href="index.html#top">Leaderboard</a></nav></header><main class="cases-main"><section class="case-document-intro"><a class="case-back" href="index.html#cases-title">← All selected cases</a><p class="case-kicker">Process chemistry · Hard</p><h1>Reaction-calorimetry safety assessment</h1><p class="lede">Convert calibration pulses, blank dosing experiments, and reaction heat-flow traces into auditable run metrics, replicate summaries, and protocol-level scale-up decisions.</p></section><div class="case-overview-live case-visual-board calorimetry-board" aria-label="Reaction calorimetry audit workflow diagram"><header class="visual-board-heading"><span>From raw traces to an auditable decision</span><p>Every screening outcome must remain traceable to calibration, corrections, and protocol-level evidence.</p></header><div class="cal-input-row"><div><em>Input 01</em><span>Electrical pulses</span><small>heat-flow sensitivity</small></div><div><em>Input 02</em><span>Blank dosing</span><small>non-reaction heat</small></div><div><em>Input 03</em><span>Reaction runs</span><small>time + feed + events</small></div></div><div class="visual-process-row cal-process-row"><div><em>01</em><span>Calibrate</span><small>pulse-derived sensitivity</small></div><i>→</i><div><em>02</em><span>Correct</span><small>baseline + blank</small></div><i>→</i><div><em>03</em><span>Summarize</span><small>runs + replicates</small></div><i>→</i><div><em>04</em><span>Screen</span><small>declared criteria</small></div></div><div class="cal-metric-band"><span>ΔT<sub>ad</sub></span><span>MTSR</span><span>accumulation</span><span>post-feed heat</span><span>heat recovery</span><p>Derived metrics remain linked to the corrected trace and source protocol.</p></div></div><section class="case-data-strip"><div><strong>3 stages</strong><span>calibration, correction, assessment</span></div><div><strong>6 CSVs</strong><span>traceable tabular outputs</span></div><div><strong>3 plots</strong><span>heat flow and safety summaries</span></div><div><strong>1 report</strong><span>methods and screening rationale</span></div></section><section class="case-document-section"><h2>Workflow</h2><div class="case-document-body"><ol class="workflow-steps"><li><div><h3>Establish calibration</h3><p>Derive heat-flow sensitivity from electrical pulses and quantify blank dosing heat.</p></div></li><li><div><h3>Correct the time series</h3><p>Apply baseline and blank corrections while retaining run, protocol, time, feed, and event provenance.</p></div></li><li><div><h3>Derive thermal metrics</h3><p>Integrate released heat and calculate reaction enthalpy, adiabatic rise, accumulation, MTSR, post-feed heat, and recovery.</p></div></li><li><div><h3>Screen by protocol</h3><p>Summarize replicates and map each decision and reason back to declared configuration criteria.</p></div></li></ol></div></section><section class="case-document-section"><h2>Artifact contract</h2><div class="case-document-body"><div class="artifact-list"><span>analysis.py</span><span>calibration + blank CSVs</span><span>processed time series</span><span>run thermal metrics</span><span>protocol safety summary</span><span>scale-up decision table</span><span>3 diagnostic plots</span><span>reaction_calorimetry_report.md</span></div></div></section></main><footer class="site-footer" data-shared-footer></footer><script src="site-shell.js?v=20260824-03"></script></body></html>
<!doctype html><html lang="en"><head><meta charset="utf-8" /><meta name="viewport" content="width=device-width,initial-scale=1" /><meta name="description" content="FrontierChallenge case study: reaction calorimetry safety." /><title>Reaction calorimetry safety — FrontierChallenge</title><link rel="icon" href="mark.svg" type="image/svg+xml" /><link rel="stylesheet" href="styles.css?v=20260826-01" /></head><body><header class="site-header"><div class="wordmark"><img class="wordmark-mark" src="mark.svg" alt="" /><span>FrontierChallenge: A scientific workflow benchmark</span></div><nav><a href="index.html#top">Leaderboard</a></nav></header><main class="cases-main"><section class="case-document-intro"><a class="case-back" href="index.html#cases-title">← All selected cases</a><p class="case-kicker">Process chemistry · Hard</p><h1>Reaction-calorimetry safety assessment</h1><p class="lede">Convert calibration pulses, blank dosing experiments, and reaction heat-flow traces into auditable run metrics, replicate summaries, and protocol-level scale-up decisions.</p></section><div class="case-overview-live case-visual-board calorimetry-board" aria-label="Reaction calorimetry audit workflow diagram"><header class="visual-board-heading"><span>From raw traces to an auditable decision</span><p>Every screening outcome must remain traceable to calibration, corrections, and protocol-level evidence.</p></header><div class="cal-input-row"><div><em>Input 01</em><span>Electrical pulses</span><small>heat-flow sensitivity</small></div><div><em>Input 02</em><span>Blank dosing</span><small>non-reaction heat</small></div><div><em>Input 03</em><span>Reaction runs</span><small>time + feed + events</small></div></div><div class="visual-process-row cal-process-row"><div><em>01</em><span>Calibrate</span><small>pulse-derived sensitivity</small></div><i>→</i><div><em>02</em><span>Correct</span><small>baseline + blank</small></div><i>→</i><div><em>03</em><span>Summarize</span><small>runs + replicates</small></div><i>→</i><div><em>04</em><span>Screen</span><small>declared criteria</small></div></div><div class="cal-metric-band"><span>ΔT<sub>ad</sub></span><span>MTSR</span><span>accumulation</span><span>post-feed heat</span><span>heat recovery</span><p>Derived metrics remain linked to the corrected trace and source protocol.</p></div></div><section class="case-data-strip"><div><strong>3 stages</strong><span>calibration, correction, assessment</span></div><div><strong>6 CSVs</strong><span>traceable tabular outputs</span></div><div><strong>3 plots</strong><span>heat flow and safety summaries</span></div><div><strong>1 report</strong><span>methods and screening rationale</span></div></section><section class="case-document-section"><h2>Workflow</h2><div class="case-document-body"><ol class="workflow-steps"><li><div><h3>Establish calibration</h3><p>Derive heat-flow sensitivity from electrical pulses and quantify blank dosing heat.</p></div></li><li><div><h3>Correct the time series</h3><p>Apply baseline and blank corrections while retaining run, protocol, time, feed, and event provenance.</p></div></li><li><div><h3>Derive thermal metrics</h3><p>Integrate released heat and calculate reaction enthalpy, adiabatic rise, accumulation, MTSR, post-feed heat, and recovery.</p></div></li><li><div><h3>Screen by protocol</h3><p>Summarize replicates and map each decision and reason back to declared configuration criteria.</p></div></li></ol></div></section><section class="case-document-section"><h2>Artifact contract</h2><div class="case-document-body"><div class="artifact-list"><span>analysis.py</span><span>calibration + blank CSVs</span><span>processed time series</span><span>run thermal metrics</span><span>protocol safety summary</span><span>scale-up decision table</span><span>3 diagnostic plots</span><span>reaction_calorimetry_report.md</span></div></div></section></main><footer class="site-footer" data-shared-footer></footer><script src="site-shell.js?v=20260824-03"></script></body></html>
2 changes: 1 addition & 1 deletion benchmarks/frontierchallenge/site/case-cell-migration.html
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<!doctype html><html lang="en"><head><meta charset="utf-8" /><meta name="viewport" content="width=device-width,initial-scale=1" /><meta name="description" content="FrontierChallenge case study: cell migration imaging." /><title>Cell migration imaging — FrontierChallenge</title><link rel="icon" href="mark.svg" type="image/svg+xml" /><link rel="stylesheet" href="styles.css?v=20260824-03" /></head>
<!doctype html><html lang="en"><head><meta charset="utf-8" /><meta name="viewport" content="width=device-width,initial-scale=1" /><meta name="description" content="FrontierChallenge case study: cell migration imaging." /><title>Cell migration imaging — FrontierChallenge</title><link rel="icon" href="mark.svg" type="image/svg+xml" /><link rel="stylesheet" href="styles.css?v=20260826-01" /></head>
<body><header class="site-header"><div class="wordmark"><img class="wordmark-mark" src="mark.svg" alt="" /><span>FrontierChallenge: A scientific workflow benchmark</span></div><nav><a href="index.html#top">Leaderboard</a></nav></header>
<main class="cases-main"><section class="case-document-intro"><a class="case-back" href="index.html#cases-title">← All selected cases</a><p class="case-kicker">Life science · Medium</p><h1>Cell migration from time-lapse microscopy</h1><p class="lede">Turn a structured image experiment into reviewed segmentations, correctly paired migration rates, statistical comparisons, plots, and a reproducible report.</p></section>
<figure class="case-overview-figure"><img src="assets/cases/cell-migration-input.jpg" alt="Bright-field inputs at zero, twelve and twenty-four hours" /><figcaption>One control replicate across time. White closed contours were drawn by the experimenter and are part of the agent-visible input.</figcaption></figure>
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2 changes: 1 addition & 1 deletion benchmarks/frontierchallenge/site/case-eis.html
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<!doctype html><html lang="en"><head><meta charset="utf-8" /><meta name="viewport" content="width=device-width,initial-scale=1" /><meta name="description" content="FrontierChallenge case study: EIS equivalent-circuit analysis." /><title>EIS equivalent-circuit analysis — FrontierChallenge</title><link rel="icon" href="mark.svg" type="image/svg+xml" /><link rel="stylesheet" href="styles.css?v=20260824-03" /></head>
<!doctype html><html lang="en"><head><meta charset="utf-8" /><meta name="viewport" content="width=device-width,initial-scale=1" /><meta name="description" content="FrontierChallenge case study: EIS equivalent-circuit analysis." /><title>EIS equivalent-circuit analysis — FrontierChallenge</title><link rel="icon" href="mark.svg" type="image/svg+xml" /><link rel="stylesheet" href="styles.css?v=20260826-01" /></head>
<body><header class="site-header"><div class="wordmark"><img class="wordmark-mark" src="mark.svg" alt="" /><span>FrontierChallenge: A scientific workflow benchmark</span></div><nav><a href="index.html#top">Leaderboard</a></nav></header>
<main class="cases-main"><section class="case-document-intro"><a class="case-back" href="index.html#cases-title">← All selected cases</a><p class="case-kicker">Electrochemistry · Hard</p><h1>Equivalent-circuit analysis of impedance spectra</h1><p class="lede">Fit prescribed circuit families, compare them with traceable metrics and residuals, and connect the frequency response to electrochemical processes without hiding uncertainty.</p></section>
<figure class="case-overview-figure"><img src="assets/cases/eis-input.svg" alt="Raw Nyquist spectra" /><figcaption>Two raw input traces before preprocessing, candidate-circuit fitting, or model selection.</figcaption></figure>
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2 changes: 1 addition & 1 deletion benchmarks/frontierchallenge/site/case-gitt.html
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<!doctype html><html lang="en"><head><meta charset="utf-8" /><meta name="viewport" content="width=device-width,initial-scale=1" /><meta name="description" content="FrontierChallenge case study: hard-carbon GITT diffusion analysis." /><title>GITT diffusion analysis — FrontierChallenge</title><link rel="icon" href="mark.svg" type="image/svg+xml" /><link rel="stylesheet" href="styles.css?v=20260824-03" /></head>
<!doctype html><html lang="en"><head><meta charset="utf-8" /><meta name="viewport" content="width=device-width,initial-scale=1" /><meta name="description" content="FrontierChallenge case study: hard-carbon GITT diffusion analysis." /><title>GITT diffusion analysis — FrontierChallenge</title><link rel="icon" href="mark.svg" type="image/svg+xml" /><link rel="stylesheet" href="styles.css?v=20260826-01" /></head>
<body><header class="site-header"><div class="wordmark"><img class="wordmark-mark" src="mark.svg" alt="" /><span>FrontierChallenge: A scientific workflow benchmark</span></div><nav><a href="index.html#top">Leaderboard</a></nav></header>
<main class="cases-main"><section class="case-document-intro"><a class="case-back" href="index.html#cases-title">← All selected cases</a><p class="case-kicker">Electrochemistry · Hard</p><h1>Sodium-ion diffusion from GITT sequences</h1><p class="lede">Resolve pulse, rest, and relaxation segments across hard-carbon cells, assess pulse quality from measured stability, and preserve SOC-dependent transport calculations in a checkable bundle.</p></section>
<figure class="case-overview-figure"><img src="assets/cases/gitt-input.png" alt="Raw GITT voltage sequence from one hard-carbon cell" /><figcaption>A complete raw cell record showing the repeated voltage steps and relaxations before pulse segmentation, QC, or diffusion calculations.</figcaption></figure>
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2 changes: 1 addition & 1 deletion benchmarks/frontierchallenge/site/case-lfa.html
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<!doctype html><html lang="en"><head><meta charset="utf-8" /><meta name="viewport" content="width=device-width,initial-scale=1" /><meta name="description" content="FrontierChallenge case study: laser-flash thermal analysis." /><title>Laser-flash thermal analysis — FrontierChallenge</title><link rel="icon" href="mark.svg" type="image/svg+xml" /><link rel="stylesheet" href="styles.css?v=20260824-03" /></head>
<!doctype html><html lang="en"><head><meta charset="utf-8" /><meta name="viewport" content="width=device-width,initial-scale=1" /><meta name="description" content="FrontierChallenge case study: laser-flash thermal analysis." /><title>Laser-flash thermal analysis — FrontierChallenge</title><link rel="icon" href="mark.svg" type="image/svg+xml" /><link rel="stylesheet" href="styles.css?v=20260826-01" /></head>
<body><header class="site-header"><div class="wordmark"><img class="wordmark-mark" src="mark.svg" alt="" /><span>FrontierChallenge: A scientific workflow benchmark</span></div><nav><a href="index.html#top">Leaderboard</a></nav></header>
<main class="cases-main"><section class="case-document-intro"><a class="case-back" href="index.html#cases-title">← All selected cases</a><p class="case-kicker">Materials characterization · Hard</p><h1>Thermal transport from laser-flash curves</h1><p class="lede">Reassemble shuffled temperature-rise traces, judge curve quality from their shapes, and carry accepted runs through thermal diffusivity, conductivity, and sample-level statistics.</p></section>
<figure class="case-overview-figure"><img src="assets/cases/lfa-input.png" alt="Raw laser-flash temperature-rise curves" /><figcaption>One raw detector trace from each BN loading before ordering, baseline treatment, curve QC, or thermal-property calculations.</figcaption></figure>
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2 changes: 1 addition & 1 deletion benchmarks/frontierchallenge/site/case-photoredox.html
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<!doctype html><html lang="en"><head><meta charset="utf-8" /><meta name="viewport" content="width=device-width,initial-scale=1" /><meta name="description" content="FrontierChallenge case study: photoredox photon balance and quantum yield." /><title>Photoredox photon balance — FrontierChallenge</title><link rel="icon" href="mark.svg" type="image/svg+xml" /><link rel="stylesheet" href="styles.css?v=20260824-03" /></head>
<!doctype html><html lang="en"><head><meta charset="utf-8" /><meta name="viewport" content="width=device-width,initial-scale=1" /><meta name="description" content="FrontierChallenge case study: photoredox photon balance and quantum yield." /><title>Photoredox photon balance — FrontierChallenge</title><link rel="icon" href="mark.svg" type="image/svg+xml" /><link rel="stylesheet" href="styles.css?v=20260826-01" /></head>
<body><header class="site-header"><div class="wordmark"><img class="wordmark-mark" src="mark.svg" alt="" /><span>FrontierChallenge: A scientific workflow benchmark</span></div><nav><a href="index.html#top">Leaderboard</a></nav></header>
<main class="cases-main"><section class="case-document-intro"><a class="case-back" href="index.html#cases-title">← All selected cases</a><p class="case-kicker">Photochemistry · Hard</p><h1>Photoredox photon balance and quantum yield</h1><p class="lede">Connect ferrioxalate actinometry, LED emission, reaction absorbance, quantitative assays, dark controls, and an independent condition without mixing calibration, training, or validation roles.</p></section>
<figure class="case-overview-figure"><img src="assets/cases/photoredox-input.png" alt="Raw blue LED spectra from three experimental conditions" /><figcaption>Three raw pre-reaction LED spectra before dark correction, detector-response correction, spectral weighting, or photon-balance calculations.</figcaption></figure>
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2 changes: 1 addition & 1 deletion benchmarks/frontierchallenge/site/case-qnmr.html
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<!doctype html><html lang="en"><head><meta charset="utf-8" /><meta name="viewport" content="width=device-width,initial-scale=1" /><meta name="description" content="FrontierChallenge case study: quantitative NMR purity and spectral QC." /><title>qNMR purity and spectral QC — FrontierChallenge</title><link rel="icon" href="mark.svg" type="image/svg+xml" /><link rel="stylesheet" href="styles.css?v=20260824-03" /></head>
<!doctype html><html lang="en"><head><meta charset="utf-8" /><meta name="viewport" content="width=device-width,initial-scale=1" /><meta name="description" content="FrontierChallenge case study: quantitative NMR purity and spectral QC." /><title>qNMR purity and spectral QC — FrontierChallenge</title><link rel="icon" href="mark.svg" type="image/svg+xml" /><link rel="stylesheet" href="styles.css?v=20260826-01" /></head>
<body><header class="site-header"><div class="wordmark"><img class="wordmark-mark" src="mark.svg" alt="" /><span>FrontierChallenge: A scientific workflow benchmark</span></div><nav><a href="index.html#top">Leaderboard</a></nav></header>
<main class="cases-main"><section class="case-document-intro"><a class="case-back" href="index.html#cases-title">← All selected cases</a><p class="case-kicker">Analytical chemistry · Hard</p><h1>Quantitative NMR purity with spectrum-level QC</h1><p class="lede">Reference, process, and integrate replicate ¹H NMR spectra while keeping quality-control decisions, batch summaries, and every reported purity value mutually consistent.</p></section>
<figure class="case-overview-figure"><img src="assets/cases/qnmr-input.png" alt="Four raw quantitative proton NMR spectra" /><figcaption>Four agent-visible replicate spectra before reference correction, baseline processing, integration, or anomaly decisions.</figcaption></figure>
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