Deploy reliability-aware PHBV mass-loss predictor

README.md

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----
-title: Phbv Mass Loss Reliability
-emoji: 👀
-colorFrom: blue
-colorTo: yellow
-sdk: static
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: PHBV Mass-Loss Reliability Explorer
+emoji: 🧪
+colorFrom: blue
+colorTo: green
+sdk: static
+app_file: index.html
+pinned: false
+license: mit
+short_description: Study-aware PHBV mass-loss prediction
+---
+
+# PHBV Mass-Loss Reliability Explorer
+
+This public research-use Space predicts degradation-induced specimen mass/weight loss (%) for PHBV formulations. It provides single-time-point and trajectory modes, 0–100% bounds, a positive monotonic constraint on degradation time, marginal range/category warnings, and a deliberately conservative descriptive uncertainty band. Inference runs locally in the browser from an exported XGBoost tree ensemble; no prediction server is required.
+
+## Scientific boundary
+
+The output is **gravimetric mass loss**, not ultimate biodegradation, mineralisation, carbon conversion, environmental safety, or compliance with a biodegradability standard. Mass loss can include disintegration, recovery loss, leaching, and biological conversion.
+
+## Validation
+
+- Evidence base: 1,467 observations from 129 curves in 16 source studies.
+- Primary research assessment: nested leave-one-study-out validation with study-grouped inner tuning.
+- Primary macro-study MAE: 23.554 percentage points (95% study-bootstrap CI 17.421–30.251).
+- Point MAE/RMSE/$R^2$: 22.061 / 30.483 / 0.145.
+- Random-row XGBoost $R^2$ was 0.915, but this is an optimistic interpolation benchmark because related time points cross the split.
+- Nominal 90% grouped conformal intervals covered 97.6% overall, but their mean width was 91.9 percentage points and one held-out study had only 37.5% coverage.
+
+These results do not support high-stakes or study-independent certification use. The interface reports the strict grouped evidence rather than deployment-training fit.
+
+## Intended use
+
+Use the tool to explore hypotheses, inspect plausible bounded trajectory shapes, identify marginal out-of-range inputs, and prioritise experiments. Do not use it to replace laboratory testing, make regulatory or safety decisions, or infer causal effects of a formulation or environment.
+
+## Model
+
+The model is an XGBoost regressor trained on a bounded-logit target with a positive monotonic constraint on degradation time and equal total training weight per study. Categorical variables are one-hot encoded with unknown levels ignored; numeric missingness is median-imputed inside the fitted preprocessing pipeline. The interactive model is fitted on all 16 studies after the research evaluation was completed.
+
+## Citation
+
+The source data were compiled by Kotzabasaki et al. (2026), *Polymers* 18, 897: https://doi.org/10.3390/polym18070897. Cite the companion reliability-analysis manuscript and archived code/data release when their final bibliographic records are available.

browser_model.json

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index.html

@@ -1,19 +1,671 @@
 <!doctype html>
-<html>
-	<head>
-		<meta charset="utf-8" />
-		<meta name="viewport" content="width=device-width" />
-		<title>My static Space</title>
-		<link rel="stylesheet" href="style.css" />
-	</head>
-	<body>
-		<div class="card">
-			<h1>Welcome to your static Space!</h1>
-			<p>You can modify this app directly by editing <i>index.html</i> in the Files and versions tab.</p>
-			<p>
-				Also don't forget to check the
-				<a href="https://huggingface.co/docs/hub/spaces" target="_blank">Spaces documentation</a>.
-			</p>
-		</div>
-	</body>
+<html lang="en">
+<head>
+  <meta charset="utf-8">
+  <meta name="viewport" content="width=device-width, initial-scale=1">
+  <meta name="description" content="Research-use PHBV degradation-induced mass-loss prediction with study-aware validation boundaries.">
+  <link rel="icon" href="data:,">
+  <title>PHBV Mass-Loss Reliability Explorer</title>
+  <style>
+    :root {
+      color-scheme: light;
+      --paper: #f4f0e7;
+      --surface: #fffdf8;
+      --surface-2: #ebe6dc;
+      --ink: #17261f;
+      --muted: #59655f;
+      --line: #cec8bc;
+      --spruce: #1e6552;
+      --spruce-2: #164b3e;
+      --spruce-soft: #d9e8e1;
+      --clay: #b95f32;
+      --clay-soft: #f2dfd3;
+      --gold: #9a7a32;
+      --shadow: 0 18px 48px rgba(31, 45, 38, .10);
+      --radius-sm: 6px;
+      --radius-lg: 14px;
+      --font-display: Georgia, "Times New Roman", serif;
+      --font-body: Aptos, "Segoe UI", sans-serif;
+      --font-mono: "Cascadia Mono", Consolas, monospace;
+    }
+
+    [data-theme="dark"] {
+      color-scheme: dark;
+      --paper: #15211c;
+      --surface: #1d2b25;
+      --surface-2: #26362f;
+      --ink: #edf1eb;
+      --muted: #b6c2bb;
+      --line: #405048;
+      --spruce: #7cc4a8;
+      --spruce-2: #a5d7c3;
+      --spruce-soft: #29483d;
+      --clay: #ed9568;
+      --clay-soft: #513627;
+      --gold: #cfb66e;
+      --shadow: 0 18px 48px rgba(0, 0, 0, .28);
+    }
+
+    * { box-sizing: border-box; }
+    html { scroll-behavior: smooth; }
+    body {
+      margin: 0;
+      background:
+        linear-gradient(rgba(23, 38, 31, .035) 1px, transparent 1px),
+        linear-gradient(90deg, rgba(23, 38, 31, .035) 1px, transparent 1px),
+        var(--paper);
+      background-size: 32px 32px;
+      color: var(--ink);
+      font-family: var(--font-body);
+      font-size: 17px;
+      line-height: 1.55;
+      text-wrap: pretty;
+    }
+
+    button, input, select { font: inherit; }
+    button, a, input, select, summary { -webkit-tap-highlight-color: transparent; }
+    :focus-visible { outline: 3px solid var(--clay); outline-offset: 3px; }
+
+    .shell { width: min(1180px, calc(100% - 32px)); margin: 0 auto; }
+    .topbar {
+      display: flex;
+      align-items: center;
+      justify-content: space-between;
+      min-height: 64px;
+      border-bottom: 1px solid var(--line);
+    }
+    .wordmark {
+      display: flex;
+      align-items: center;
+      gap: 12px;
+      color: var(--ink);
+      font-weight: 700;
+      letter-spacing: .01em;
+    }
+    .mark {
+      display: grid;
+      place-items: center;
+      width: 30px;
+      height: 30px;
+      border: 1px solid var(--spruce);
+      border-radius: 50%;
+      color: var(--spruce);
+      font-family: var(--font-mono);
+      font-size: 12px;
+      font-weight: 700;
+    }
+    .quiet-button {
+      min-height: 42px;
+      padding: 8px 12px;
+      border: 1px solid var(--line);
+      border-radius: var(--radius-sm);
+      background: var(--surface);
+      color: var(--ink);
+      cursor: pointer;
+      transition: transform 160ms ease, border-color 160ms ease, background 160ms ease;
+    }
+    .quiet-button:hover { border-color: var(--spruce); background: var(--spruce-soft); }
+    .quiet-button:active { transform: translateY(1px); }
+
+    .hero {
+      display: grid;
+      grid-template-columns: minmax(0, 1.5fr) minmax(280px, .72fr);
+      gap: clamp(32px, 6vw, 80px);
+      padding: clamp(56px, 9vw, 112px) 0 48px;
+      align-items: end;
+    }
+    .eyebrow {
+      margin: 0 0 14px;
+      color: var(--spruce);
+      font-family: var(--font-mono);
+      font-size: 12px;
+      font-weight: 700;
+      letter-spacing: .12em;
+      text-transform: uppercase;
+    }
+    h1, h2, h3 { font-family: var(--font-display); font-weight: 500; line-height: 1.08; }
+    h1 { margin: 0; font-size: clamp(44px, 7vw, 82px); letter-spacing: -.045em; }
+    h2 { margin: 0 0 12px; font-size: clamp(28px, 4vw, 44px); letter-spacing: -.025em; }
+    h3 { margin: 0; font-size: 24px; }
+    .lede { max-width: 760px; margin: 24px 0 0; color: var(--muted); font-size: clamp(18px, 2.1vw, 23px); }
+    .endpoint-note {
+      padding: 24px;
+      border-top: 4px solid var(--clay);
+      background: var(--surface);
+      box-shadow: var(--shadow);
+    }
+    .endpoint-note strong { display: block; margin-bottom: 8px; color: var(--clay); font-family: var(--font-mono); font-size: 12px; letter-spacing: .08em; text-transform: uppercase; }
+    .endpoint-note p { margin: 0; }
+
+    .evidence-strip {
+      display: grid;
+      grid-template-columns: repeat(4, 1fr);
+      margin: 0 auto 40px;
+      border: 1px solid var(--line);
+      background: var(--surface);
+    }
+    .evidence-item { min-height: 124px; padding: 22px; border-right: 1px solid var(--line); }
+    .evidence-item:last-child { border-right: 0; }
+    .metric { display: block; margin-bottom: 8px; font-family: var(--font-display); font-size: 34px; line-height: 1; }
+    .metric-label { color: var(--muted); font-size: 14px; }
+
+    .warning-banner {
+      display: grid;
+      grid-template-columns: auto 1fr;
+      gap: 16px;
+      margin-bottom: 40px;
+      padding: 22px 24px;
+      border: 1px solid color-mix(in srgb, var(--clay) 45%, var(--line));
+      border-radius: var(--radius-sm);
+      background: var(--clay-soft);
+    }
+    .warning-code { color: var(--clay); font-family: var(--font-mono); font-size: 13px; font-weight: 700; }
+    .warning-banner p { margin: 0; }
+
+    .workspace {
+      overflow: hidden;
+      margin-bottom: 56px;
+      border: 1px solid var(--line);
+      border-radius: var(--radius-lg);
+      background: var(--surface);
+      box-shadow: var(--shadow);
+    }
+    .tabs { display: flex; gap: 0; border-bottom: 1px solid var(--line); background: var(--surface-2); }
+    .tab {
+      min-height: 54px;
+      padding: 12px 22px;
+      border: 0;
+      border-right: 1px solid var(--line);
+      background: transparent;
+      color: var(--muted);
+      cursor: pointer;
+      font-weight: 650;
+      transition: background 160ms ease, color 160ms ease;
+    }
+    .tab:hover { background: var(--surface); color: var(--ink); }
+    .tab[aria-selected="true"] { background: var(--surface); color: var(--spruce-2); box-shadow: inset 0 -3px var(--spruce); }
+    .panel { display: none; }
+    .panel.active { display: block; animation: enter 220ms ease both; }
+    @keyframes enter { from { opacity: 0; transform: translateY(4px); } to { opacity: 1; transform: none; } }
+
+    .tool-grid { display: grid; grid-template-columns: minmax(0, 1.16fr) minmax(340px, .84fr); min-height: 660px; }
+    .form-pane { padding: clamp(24px, 4vw, 44px); border-right: 1px solid var(--line); }
+    .result-pane { padding: clamp(24px, 4vw, 44px); background: color-mix(in srgb, var(--spruce-soft) 32%, var(--surface)); }
+    .section-intro { margin-bottom: 30px; }
+    .section-intro p { margin: 8px 0 0; color: var(--muted); }
+    .field-groups { display: grid; gap: 22px; }
+    fieldset { margin: 0; padding: 0; border: 0; }
+    legend {
+      width: 100%;
+      margin-bottom: 12px;
+      padding-bottom: 8px;
+      border-bottom: 1px solid var(--line);
+      color: var(--spruce-2);
+      font-family: var(--font-mono);
+      font-size: 12px;
+      font-weight: 700;
+      letter-spacing: .08em;
+      text-transform: uppercase;
+    }
+    .fields { display: grid; grid-template-columns: repeat(2, minmax(0, 1fr)); gap: 14px 16px; }
+    .field { min-width: 0; }
+    label { display: block; margin-bottom: 6px; font-size: 14px; font-weight: 650; }
+    input, select {
+      width: 100%;
+      min-height: 46px;
+      padding: 9px 11px;
+      border: 1px solid var(--line);
+      border-radius: var(--radius-sm);
+      background: var(--surface);
+      color: var(--ink);
+      transition: border-color 160ms ease, box-shadow 160ms ease;
+    }
+    input:hover, select:hover { border-color: var(--spruce); }
+    input:focus, select:focus { border-color: var(--spruce); box-shadow: 0 0 0 3px color-mix(in srgb, var(--spruce) 18%, transparent); outline: 0; }
+    .range { display: block; margin-top: 4px; color: var(--muted); font-family: var(--font-mono); font-size: 11px; }
+    .primary-button {
+      width: 100%;
+      min-height: 52px;
+      margin-top: 26px;
+      border: 1px solid var(--spruce-2);
+      border-radius: var(--radius-sm);
+      background: var(--spruce-2);
+      color: var(--surface);
+      cursor: pointer;
+      font-weight: 750;
+      letter-spacing: .01em;
+      transition: transform 160ms ease, filter 160ms ease, box-shadow 160ms ease;
+    }
+    [data-theme="dark"] .primary-button { color: #13221b; }
+    .primary-button:hover { filter: brightness(1.08); box-shadow: 0 10px 24px rgba(22, 75, 62, .18); transform: translateY(-1px); }
+    .primary-button:active { transform: translateY(1px); }
+    .primary-button:disabled { cursor: wait; opacity: .62; transform: none; }
+
+    .empty-state { min-height: 340px; display: grid; place-items: center; text-align: center; color: var(--muted); }
+    .empty-state .ring { display: grid; place-items: center; width: 92px; height: 92px; margin: 0 auto 20px; border: 1px solid var(--line); border-radius: 50%; font-family: var(--font-mono); color: var(--spruce); }
+    .result-block[hidden], .error-block[hidden] { display: none; }
+    .result-kicker { color: var(--spruce-2); font-family: var(--font-mono); font-size: 12px; font-weight: 700; letter-spacing: .1em; text-transform: uppercase; }
+    .prediction { margin: 10px 0 6px; font-family: var(--font-display); font-size: clamp(52px, 7vw, 78px); line-height: 1; letter-spacing: -.04em; }
+    .prediction small { font-family: var(--font-body); font-size: 18px; letter-spacing: 0; }
+    .band { margin: 0 0 26px; color: var(--muted); }
+    .band strong { color: var(--ink); }
+    .notes { margin: 20px 0 0; padding: 18px; border: 1px solid var(--line); border-radius: var(--radius-sm); background: var(--surface); }
+    .notes h4 { margin: 0 0 10px; font-size: 15px; }
+    .notes ul { margin: 0; padding-left: 20px; }
+    .notes li + li { margin-top: 6px; }
+    .error-block { padding: 18px; border: 1px solid var(--clay); border-radius: var(--radius-sm); background: var(--clay-soft); color: var(--ink); }
+
+    .trajectory-pane { padding: clamp(24px, 4vw, 44px); }
+    .trajectory-layout { display: grid; grid-template-columns: minmax(340px, .72fr) minmax(0, 1.28fr); gap: 30px; }
+    .time-fields { display: grid; grid-template-columns: repeat(3, 1fr); gap: 12px; margin-bottom: 22px; }
+    .chart-card { min-height: 420px; padding: 18px; border: 1px solid var(--line); border-radius: var(--radius-sm); background: var(--surface); }
+    #trajectoryChart { display: block; width: 100%; height: auto; overflow: visible; }
+    .chart-legend { display: flex; flex-wrap: wrap; gap: 14px; margin: 12px 0 0; color: var(--muted); font-size: 13px; }
+    .legend-line::before, .legend-band::before { content: ""; display: inline-block; width: 24px; height: 3px; margin-right: 7px; vertical-align: middle; background: var(--spruce); }
+    .legend-band::before { height: 10px; background: var(--spruce-soft); border: 1px solid var(--spruce); }
+    .table-toolbar { display: flex; justify-content: space-between; align-items: center; gap: 12px; margin: 22px 0 10px; }
+    .table-wrap { max-height: 320px; overflow: auto; border: 1px solid var(--line); border-radius: var(--radius-sm); }
+    table { width: 100%; border-collapse: collapse; font-variant-numeric: tabular-nums; font-size: 14px; }
+    th, td { padding: 9px 12px; border-bottom: 1px solid var(--line); text-align: right; white-space: nowrap; }
+    th { position: sticky; top: 0; background: var(--surface-2); color: var(--ink); font-family: var(--font-mono); font-size: 11px; letter-spacing: .04em; }
+    th:first-child, td:first-child { text-align: left; }
+
+    .methods { display: grid; grid-template-columns: .65fr 1.35fr; gap: clamp(28px, 6vw, 72px); padding: 64px 0 80px; }
+    .methods-copy p { color: var(--muted); }
+    details { border-top: 1px solid var(--line); }
+    details:last-child { border-bottom: 1px solid var(--line); }
+    summary { padding: 18px 0; cursor: pointer; font-weight: 700; list-style: none; }
+    summary::after { content: "+"; float: right; color: var(--spruce); font-family: var(--font-mono); }
+    details[open] summary::after { content: "−"; }
+    details p, details ul { color: var(--muted); }
+    details > :not(summary) { margin-top: 0; margin-bottom: 20px; }
+
+    footer { padding: 28px 0 44px; border-top: 1px solid var(--line); color: var(--muted); font-size: 14px; }
+    footer a { color: var(--spruce-2); }
+
+    @media (max-width: 900px) {
+      .hero, .tool-grid, .trajectory-layout, .methods { grid-template-columns: 1fr; }
+      .evidence-strip { grid-template-columns: repeat(2, 1fr); }
+      .evidence-item:nth-child(2) { border-right: 0; }
+      .evidence-item:nth-child(-n+2) { border-bottom: 1px solid var(--line); }
+      .form-pane { border-right: 0; border-bottom: 1px solid var(--line); }
+      .result-pane { min-height: 430px; }
+    }
+    @media (max-width: 600px) {
+      body { font-size: 16px; }
+      .shell { width: min(100% - 20px, 1180px); }
+      .topbar { min-height: 58px; }
+      .wordmark span:last-child { display: none; }
+      .hero { padding-top: 48px; }
+      .evidence-strip, .fields, .time-fields { grid-template-columns: 1fr; }
+      .evidence-item { border-right: 0; border-bottom: 1px solid var(--line); }
+      .evidence-item:last-child { border-bottom: 0; }
+      .warning-banner { grid-template-columns: 1fr; }
+      .tabs { overflow-x: auto; }
+      .tab { flex: 1 0 auto; min-height: 48px; padding: 10px 14px; }
+      .form-pane, .result-pane, .trajectory-pane { padding: 22px 18px; }
+      .table-toolbar { align-items: flex-start; flex-direction: column; }
+    }
+    @media (prefers-reduced-motion: reduce) {
+      *, *::before, *::after { scroll-behavior: auto !important; animation: none !important; transition-duration: .01ms !important; }
+    }
+  </style>
+</head>
+<body>
+  <header class="shell topbar">
+    <div class="wordmark"><span class="mark" aria-hidden="true">P/H</span><span>PHBV Reliability Explorer</span></div>
+    <button id="themeToggle" class="quiet-button" type="button" aria-pressed="false">Switch theme</button>
+  </header>
+
+  <main>
+    <section class="shell hero" aria-labelledby="pageTitle">
+      <div>
+        <p class="eyebrow">Study-aware polymer modelling</p>
+        <h1 id="pageTitle">Predict a trajectory.<br>Keep the uncertainty visible.</h1>
+        <p class="lede">A browser-native, bounded and time-monotonic XGBoost model for literature-derived PHBV degradation-induced mass loss.</p>
+      </div>
+      <aside class="endpoint-note">
+        <strong>Endpoint boundary</strong>
+        <p>Mass loss can reflect disintegration, leaching, fragment recovery, and biological conversion. It is not proof of ultimate biodegradation or mineralisation.</p>
+      </aside>
+    </section>
+
+    <section class="shell evidence-strip" aria-label="Strict validation summary">
+      <div class="evidence-item"><span class="metric">16</span><span class="metric-label">independent source studies</span></div>
+      <div class="evidence-item"><span class="metric">23.55</span><span class="metric-label">macro-study MAE, percentage points</span></div>
+      <div class="evidence-item"><span class="metric">0.145</span><span class="metric-label">nested LOSO point R²</span></div>
+      <div class="evidence-item"><span class="metric">91.9</span><span class="metric-label">mean width of nominal 90% intervals</span></div>
+    </section>
+
+    <section class="shell warning-banner" aria-label="Research use warning">
+      <span class="warning-code">RESEARCH USE</span>
+      <p>Cross-study errors were large and heterogeneous. Use this tool to explore hypotheses and plan experiments—not for certification, regulatory decisions, safety claims, causal inference, or replacement of laboratory tests.</p>
+    </section>
+
+    <section class="shell workspace" aria-label="Prediction workspace">
+      <div class="tabs" role="tablist" aria-label="Prediction mode">
+        <button class="tab" id="singleTab" role="tab" aria-controls="singlePanel" aria-selected="true">Single time point</button>
+        <button class="tab" id="trajectoryTab" role="tab" aria-controls="trajectoryPanel" aria-selected="false">Full trajectory</button>
+      </div>
+
+      <section id="singlePanel" class="panel active" role="tabpanel" aria-labelledby="singleTab">
+        <div class="tool-grid">
+          <div class="form-pane">
+            <div class="section-intro"><h2>Describe one observation</h2><p>All fields mirror the released modelling table. Recorded marginal ranges are shown beneath numeric inputs.</p></div>
+            <form id="singleForm" class="field-groups"></form>
+            <button id="predictSingle" class="primary-button" type="button">Calculate mass-loss prediction</button>
+          </div>
+          <div class="result-pane" aria-live="polite">
+            <div id="singleEmpty" class="empty-state"><div><div class="ring">0–100</div><strong>Ready for a study-aware estimate</strong><p>Enter a scenario, then calculate. The reliability band will remain visible beside the point estimate.</p></div></div>
+            <div id="singleResult" class="result-block" hidden>
+              <span class="result-kicker">Bounded monotonic estimate</span>
+              <div class="prediction"><span id="predictionValue">—</span><small>% mass loss</small></div>
+              <p class="band"><strong id="intervalValue">—</strong><br>Descriptive 90% reliability band; not guaranteed for a new study.</p>
+              <div id="singleNotes" class="notes"></div>
+            </div>
+            <div id="singleError" class="error-block" hidden role="alert"></div>
+          </div>
+        </div>
+      </section>
+
+      <section id="trajectoryPanel" class="panel" role="tabpanel" aria-labelledby="trajectoryTab">
+        <div class="trajectory-pane">
+          <div class="section-intro"><h2>Trace a fixed-profile trajectory</h2><p>Only time changes along the curve. Every other formulation and environmental descriptor remains fixed.</p></div>
+          <div class="trajectory-layout">
+            <div>
+              <div class="time-fields">
+                <div class="field"><label for="startTime">Start day</label><input id="startTime" type="number" value="0" step="1"><span class="range">Suggested 0–360</span></div>
+                <div class="field"><label for="endTime">End day</label><input id="endTime" type="number" value="180" step="1"><span class="range">Must exceed start</span></div>
+                <div class="field"><label for="pointCount">Points</label><input id="pointCount" type="number" value="61" min="2" max="200" step="1"><span class="range">2–200</span></div>
+              </div>
+              <form id="trajectoryForm" class="field-groups"></form>
+              <button id="predictTrajectory" class="primary-button" type="button">Generate bounded trajectory</button>
+              <div id="trajectoryNotes" class="notes" hidden aria-live="polite"></div>
+              <div id="trajectoryError" class="error-block" hidden role="alert"></div>
+            </div>
+            <div>
+              <div class="chart-card">
+                <svg id="trajectoryChart" viewBox="0 0 800 430" role="img" aria-label="Predicted PHBV mass-loss trajectory with descriptive interval">
+                  <text x="400" y="215" text-anchor="middle" fill="currentColor" opacity=".55">Generate a trajectory to populate the chart</text>
+                </svg>
+                <div class="chart-legend"><span class="legend-line">Prediction</span><span class="legend-band">Descriptive 90% band</span></div>
+              </div>
+              <div id="tableSection" hidden>
+                <div class="table-toolbar"><strong>Trajectory values</strong><button id="downloadCsv" class="quiet-button" type="button">Download CSV</button></div>
+                <div class="table-wrap"><table><thead><tr><th>Day</th><th>Prediction (%)</th><th>90% lower</th><th>90% upper</th></tr></thead><tbody id="trajectoryRows"></tbody></table></div>
+              </div>
+            </div>
+          </div>
+        </div>
+      </section>
+    </section>
+
+    <section class="shell methods" aria-labelledby="methodTitle">
+      <div class="methods-copy"><p class="eyebrow">Read before use</p><h2 id="methodTitle">A model card inside the interface</h2><p>The page reports the strict research estimate, not training fit. Browser inference keeps the method accessible without hiding its evidential limits.</p></div>
+      <div>
+        <details open><summary>What the model guarantees</summary><p>Predictions remain within 0–100% through a bounded-logit target transform and are nondecreasing with degradation time for fixed descriptors. These are output-shape guarantees, not guarantees of accuracy.</p></details>
+        <details><summary>How it was evaluated</summary><p>The primary analysis used 16 outer leave-one-study-out folds with study-grouped inner tuning. Macro-study MAE was 23.554 percentage points (95% study-bootstrap CI 17.421–30.251). Random-row R² of 0.915 is shown only as an optimistic interpolation benchmark.</p></details>
+        <details><summary>Why the interval is so broad</summary><p>The nominal 90% grouped conformal intervals covered 97.6% overall but averaged 91.9 percentage points wide. One held-out study achieved only 37.5% coverage. The displayed band uses a training-side median residual quantile and is deliberately called descriptive.</p></details>
+        <details><summary>What applicability notes mean</summary><p>Range and category checks can flag obvious departures from the recorded evidence. They cannot detect every study shift, omitted protocol variable, or new material–environment interaction, and they do not certify a prediction as reliable.</p></details>
+        <details><summary>Privacy and computation</summary><p>The model, preprocessing map, and tree traversal run locally in this browser. Inputs are not sent to a prediction API. The static files are hosted by Hugging Face Spaces.</p></details>
+      </div>
+    </section>
+  </main>
+
+  <footer>
+    <div class="shell">Source corpus: <a href="https://doi.org/10.3390/polym18070897" rel="noopener">Kotzabasaki et al. (2026)</a>. Companion reliability manuscript and archival repository citation will be added after publication. Versioned interface: browser XGBoost export v1.</div>
+  </footer>
+
+  <script>
+    "use strict";
+
+    const featureLabels = {
+      degradation_time_days: "Degradation time (days)", adjusted_hb_ratio_formulation_mol: "Adjusted HB ratio (mol%)",
+      adjusted_hv_ratio_formulation_mol: "Adjusted HV ratio (mol%)", t_deg: "Temperature (°C)",
+      additive1_percentage_wt: "Additive 1 (wt%)", additive2_percentage_wt: "Additive 2 (wt%)",
+      additive3_percentage_wt: "Additive 3 (wt%)", degradation_condition: "Oxygen condition",
+      degradation_mechanism: "Recorded degradation mechanism", additives: "Any additives?",
+      degradation_environment: "Environment", additive_type_1: "Additive type 1", additive_type_2: "Additive type 2",
+      additive_type_3: "Additive type 3", sample_shape_morphology: "Specimen morphology",
+      pha_degrading_microbes: "PHA-degrading microbes", experimental_scale: "Experimental scale"
+    };
+    const defaults = {
+      degradation_time_days: 30, adjusted_hb_ratio_formulation_mol: 90, adjusted_hv_ratio_formulation_mol: 10,
+      t_deg: 27, additive1_percentage_wt: 0, additive2_percentage_wt: 0, additive3_percentage_wt: 0,
+      degradation_condition: "aerobic", degradation_mechanism: "microbial_enzymatic", additives: "no",
+      degradation_environment: "soil", additive_type_1: "not_applicable", additive_type_2: "not_applicable",
+      additive_type_3: "not_applicable", sample_shape_morphology: "films",
+      pha_degrading_microbes: "diverse_environmental", experimental_scale: "lab"
+    };
+    const groups = {
+      "Time and formulation": ["degradation_time_days", "adjusted_hb_ratio_formulation_mol", "adjusted_hv_ratio_formulation_mol", "t_deg"],
+      "Experimental context": ["degradation_condition", "degradation_mechanism", "degradation_environment", "sample_shape_morphology", "pha_degrading_microbes", "experimental_scale"],
+      "Additives": ["additives", "additive1_percentage_wt", "additive_type_1", "additive2_percentage_wt", "additive_type_2", "additive3_percentage_wt", "additive_type_3"]
+    };
+    let metadata;
+    let browserModel;
+    let latestRows = [];
+
+    const $ = id => document.getElementById(id);
+    const escapeHtml = value => String(value).replace(/[&<>'"]/g, character => ({"&":"&amp;","<":"&lt;",">":"&gt;","'":"&#39;",'"':"&quot;"})[character]);
+
+    function fieldMarkup(feature, prefix) {
+      const id = `${prefix}_${feature}`;
+      if (metadata.numeric_features.includes(feature)) {
+        const range = metadata.numeric_ranges[feature];
+        const step = feature === "degradation_time_days" || feature === "t_deg" ? 1 : .1;
+        return `<div class="field"><label for="${id}">${featureLabels[feature]}</label><input id="${id}" name="${feature}" type="number" value="${defaults[feature]}" step="${step}"><span class="range">Recorded ${range.minimum}–${range.maximum}</span></div>`;
+      }
+      const options = metadata.categorical_levels[feature].map(level => `<option value="${escapeHtml(level)}"${level === defaults[feature] ? " selected" : ""}>${escapeHtml(level.replaceAll("_", " "))}</option>`).join("");
+      return `<div class="field"><label for="${id}">${featureLabels[feature]}</label><select id="${id}" name="${feature}">${options}</select></div>`;
+    }
+
+    function renderForm(formId, prefix, excludeTime) {
+      const form = $(formId);
+      form.innerHTML = Object.entries(groups).map(([name, features]) => {
+        const visible = features.filter(feature => !(excludeTime && feature === "degradation_time_days"));
+        return `<fieldset><legend>${name}</legend><div class="fields">${visible.map(feature => fieldMarkup(feature, prefix)).join("")}</div></fieldset>`;
+      }).join("");
+    }
+
+    function readForm(formId, timeOverride) {
+      const data = new FormData($(formId));
+      const record = {};
+      metadata.features.forEach(feature => {
+        if (feature === "degradation_time_days" && timeOverride !== undefined) record[feature] = Number(timeOverride);
+        else if (metadata.numeric_features.includes(feature)) record[feature] = Number(data.get(feature));
+        else record[feature] = String(data.get(feature));
+      });
+      for (const feature of metadata.numeric_features) {
+        if (!Number.isFinite(record[feature])) throw new Error(`${featureLabels[feature]} must be a finite number.`);
+      }
+      return record;
+    }
+
+    function transform(record) {
+      const vector = [];
+      browserModel.numeric_features.forEach((feature, index) => {
+        const value = Number(record[feature]);
+        vector.push(Number.isFinite(value) ? value : browserModel.numeric_imputer_medians[index]);
+      });
+      browserModel.categorical_features.forEach((feature, index) => {
+        const selected = String(record[feature]);
+        browserModel.encoder_categories[index].forEach(category => vector.push(selected === category ? 1 : 0));
+      });
+      if (vector.length !== browserModel.num_transformed_features) throw new Error("The browser preprocessing map is inconsistent with the model.");
+      return vector;
+    }
+
+    function predict(record) {
+      const vector = transform(record);
+      let margin = browserModel.base_score;
+      for (const tree of browserModel.trees) {
+        let node = 0;
+        while (tree.left[node] !== -1) {
+          const value = vector[tree.split_index[node]];
+          const goLeft = Number.isNaN(value) ? Boolean(tree.default_left[node]) : value < tree.split_condition[node];
+          node = goLeft ? tree.left[node] : tree.right[node];
+        }
+        margin += tree.split_condition[node];
+      }
+      const epsilon = browserModel.target_epsilon;
+      const probability = 1 / (1 + Math.exp(-Math.max(-40, Math.min(40, margin))));
+      return probability * (100 + 2 * epsilon) - epsilon;
+    }
+
+    function applicabilityNotes(record) {
+      const notes = [];
+      metadata.numeric_features.forEach(feature => {
+        const {minimum, maximum} = metadata.numeric_ranges[feature];
+        if (record[feature] < minimum || record[feature] > maximum) notes.push(`${featureLabels[feature]}=${record[feature]} is outside the recorded range ${minimum}–${maximum}.`);
+      });
+      metadata.categorical_features.forEach(feature => {
+        if (!metadata.categorical_levels[feature].includes(record[feature])) notes.push(`${featureLabels[feature]} is an unseen category.`);
+      });
+      const additiveTotal = record.additive1_percentage_wt + record.additive2_percentage_wt + record.additive3_percentage_wt;
+      if (record.additives === "no" && additiveTotal > 0) notes.push("Additives is 'no', but at least one additive percentage is positive.");
+      if (record.additives === "yes" && additiveTotal === 0) notes.push("Additives is 'yes', but all three recorded percentages are zero.");
+      if (!notes.length) notes.push("All values are within recorded marginal ranges and category levels. This does not guarantee study-level similarity or accuracy.");
+      return notes;
+    }
+
+    function notesMarkup(notes) { return `<h4>Applicability notes</h4><ul>${notes.map(note => `<li>${escapeHtml(note)}</li>`).join("")}</ul>`; }
+
+    function showSingleError(error) {
+      $("singleEmpty").hidden = true; $("singleResult").hidden = true; $("singleError").hidden = false;
+      $("singleError").textContent = error.message || String(error);
+    }
+
+    function runSingle() {
+      const button = $("predictSingle");
+      button.disabled = true; button.textContent = "Calculating…";
+      try {
+        const record = readForm("singleForm");
+        const value = predict(record);
+        const halfWidth = metadata.descriptive_interval_half_widths["0.90"];
+        const lower = Math.max(0, value - halfWidth);
+        const upper = Math.min(100, value + halfWidth);
+        $("predictionValue").textContent = value.toFixed(2);
+        $("intervalValue").textContent = `${lower.toFixed(2)}% to ${upper.toFixed(2)}%`;
+        $("singleNotes").innerHTML = notesMarkup(applicabilityNotes(record));
+        $("singleEmpty").hidden = true; $("singleError").hidden = true; $("singleResult").hidden = false;
+      } catch (error) { showSingleError(error); }
+      finally { button.disabled = false; button.textContent = "Calculate mass-loss prediction"; }
+    }
+
+    function svgNode(name, attributes = {}, text = "") {
+      const node = document.createElementNS("http://www.w3.org/2000/svg", name);
+      Object.entries(attributes).forEach(([key, value]) => node.setAttribute(key, value));
+      if (text) node.textContent = text;
+      return node;
+    }
+
+    function drawChart(rows) {
+      const svg = $("trajectoryChart");
+      svg.replaceChildren();
+      const width = 800, height = 430, left = 68, right = 20, top = 24, bottom = 58;
+      const innerWidth = width - left - right, innerHeight = height - top - bottom;
+      const minX = rows[0].day, maxX = rows.at(-1).day;
+      const x = value => left + (value - minX) / (maxX - minX) * innerWidth;
+      const y = value => top + (100 - value) / 100 * innerHeight;
+      for (let tick = 0; tick <= 100; tick += 25) {
+        svg.append(svgNode("line", {x1:left, x2:width-right, y1:y(tick), y2:y(tick), stroke:"currentColor", opacity:".12"}));
+        svg.append(svgNode("text", {x:left-12, y:y(tick)+4, "text-anchor":"end", fill:"currentColor", opacity:".65", "font-size":"12"}, String(tick)));
+      }
+      for (let i = 0; i <= 4; i++) {
+        const value = minX + (maxX - minX) * i / 4;
+        svg.append(svgNode("text", {x:x(value), y:height-24, "text-anchor":"middle", fill:"currentColor", opacity:".65", "font-size":"12"}, value.toFixed(value % 1 ? 1 : 0)));
+      }
+      const upper = rows.map(row => `${x(row.day)},${y(row.upper)}`).join(" ");
+      const lower = [...rows].reverse().map(row => `${x(row.day)},${y(row.lower)}`).join(" ");
+      svg.append(svgNode("polygon", {points:`${upper} ${lower}`, fill:"var(--spruce-soft)", stroke:"var(--spruce)", "stroke-opacity":".35"}));
+      const line = rows.map((row, index) => `${index ? "L" : "M"}${x(row.day)} ${y(row.prediction)}`).join(" ");
+      svg.append(svgNode("path", {d:line, fill:"none", stroke:"var(--spruce)", "stroke-width":"4", "stroke-linecap":"round", "stroke-linejoin":"round"}));
+      svg.append(svgNode("line", {x1:left, x2:left, y1:top, y2:height-bottom, stroke:"currentColor", opacity:".55"}));
+      svg.append(svgNode("line", {x1:left, x2:width-right, y1:height-bottom, y2:height-bottom, stroke:"currentColor", opacity:".55"}));
+      svg.append(svgNode("text", {x:(left+width-right)/2, y:height-2, "text-anchor":"middle", fill:"currentColor", opacity:".75", "font-size":"13"}, "Degradation time (days)"));
+      const yLabel = svgNode("text", {x:15, y:(top+height-bottom)/2, "text-anchor":"middle", fill:"currentColor", opacity:".75", "font-size":"13", transform:`rotate(-90 15 ${(top+height-bottom)/2})`}, "Predicted mass loss (%)");
+      svg.append(yLabel);
+    }
+
+    function renderTable(rows) {
+      $("trajectoryRows").innerHTML = rows.map(row => `<tr><td>${row.day.toFixed(3)}</td><td>${row.prediction.toFixed(3)}</td><td>${row.lower.toFixed(3)}</td><td>${row.upper.toFixed(3)}</td></tr>`).join("");
+      $("tableSection").hidden = false;
+    }
+
+    function runTrajectory() {
+      const button = $("predictTrajectory");
+      button.disabled = true; button.textContent = "Generating…";
+      $("trajectoryError").hidden = true;
+      try {
+        const start = Number($("startTime").value), end = Number($("endTime").value), points = Number($("pointCount").value);
+        if (!Number.isFinite(start) || !Number.isFinite(end) || end <= start) throw new Error("End day must be greater than start day.");
+        if (!Number.isInteger(points) || points < 2 || points > 200) throw new Error("Points must be an integer between 2 and 200.");
+        const halfWidth = metadata.descriptive_interval_half_widths["0.90"];
+        latestRows = [];
+        for (let index = 0; index < points; index++) {
+          const day = start + (end - start) * index / (points - 1);
+          const record = readForm("trajectoryForm", day);
+          const prediction = predict(record);
+          latestRows.push({day, prediction, lower:Math.max(0,prediction-halfWidth), upper:Math.min(100,prediction+halfWidth)});
+        }
+        drawChart(latestRows); renderTable(latestRows);
+        const noteRecord = readForm("trajectoryForm", start);
+        $("trajectoryNotes").innerHTML = notesMarkup(applicabilityNotes(noteRecord));
+        $("trajectoryNotes").hidden = false;
+      } catch (error) {
+        $("trajectoryError").textContent = error.message || String(error); $("trajectoryError").hidden = false;
+      } finally { button.disabled = false; button.textContent = "Generate bounded trajectory"; }
+    }
+
+    function downloadCsv() {
+      if (!latestRows.length) return;
+      const lines = ["time_days,prediction_pct,descriptive_90_lower,descriptive_90_upper", ...latestRows.map(row => [row.day,row.prediction,row.lower,row.upper].map(value => value.toFixed(6)).join(","))];
+      const blob = new Blob([lines.join("\n")], {type:"text/csv;charset=utf-8"});
+      const url = URL.createObjectURL(blob);
+      const link = document.createElement("a"); link.href = url; link.download = "phbv_mass_loss_trajectory.csv"; link.click();
+      setTimeout(() => URL.revokeObjectURL(url), 0);
+    }
+
+    function switchTab(target) {
+      const single = target === "single";
+      $("singleTab").setAttribute("aria-selected", String(single));
+      $("trajectoryTab").setAttribute("aria-selected", String(!single));
+      $("singlePanel").classList.toggle("active", single);
+      $("trajectoryPanel").classList.toggle("active", !single);
+    }
+
+    function toggleTheme() {
+      const dark = document.documentElement.dataset.theme !== "dark";
+      document.documentElement.dataset.theme = dark ? "dark" : "light";
+      $("themeToggle").setAttribute("aria-pressed", String(dark));
+      $("themeToggle").textContent = dark ? "Use paper theme" : "Use ink theme";
+      localStorage.setItem("phbv-theme", dark ? "dark" : "light");
+      if (latestRows.length) drawChart(latestRows);
+    }
+
+    async function initialise() {
+      try {
+        const [metadataResponse, modelResponse] = await Promise.all([fetch("model_metadata.json"), fetch("browser_model.json")]);
+        if (!metadataResponse.ok || !modelResponse.ok) throw new Error("Model files could not be loaded.");
+        [metadata, browserModel] = await Promise.all([metadataResponse.json(), modelResponse.json()]);
+        renderForm("singleForm", "single", false);
+        renderForm("trajectoryForm", "trajectory", true);
+      } catch (error) {
+        showSingleError(new Error(`Initialisation failed: ${error.message}`));
+        $("predictSingle").disabled = true; $("predictTrajectory").disabled = true;
+      }
+    }
+
+    $("singleTab").addEventListener("click", () => switchTab("single"));
+    $("trajectoryTab").addEventListener("click", () => switchTab("trajectory"));
+    $("predictSingle").addEventListener("click", runSingle);
+    $("predictTrajectory").addEventListener("click", runTrajectory);
+    $("downloadCsv").addEventListener("click", downloadCsv);
+    $("themeToggle").addEventListener("click", toggleTheme);
+    const savedTheme = localStorage.getItem("phbv-theme");
+    if (savedTheme === "dark" || (!savedTheme && window.matchMedia("(prefers-color-scheme: dark)").matches)) toggleTheme();
+    initialise();
+  </script>
+</body>
 </html>

model_metadata.json

@@ -0,0 +1,206 @@
+{
+  "best_parameters": {
+    "colsample_bytree": 0.7449721611208636,
+    "learning_rate": 0.020824306666550746,
+    "max_depth": 3,
+    "min_child_weight": 3.2773123153428503,
+    "n_estimators": 300,
+    "reg_alpha": 0.8287375091519293,
+    "reg_lambda": 1.1369027867815908,
+    "subsample": 0.7860370513913187
+  },
+  "categorical_features": [
+    "degradation_condition",
+    "degradation_mechanism",
+    "additives",
+    "degradation_environment",
+    "additive_type_1",
+    "additive_type_2",
+    "additive_type_3",
+    "sample_shape_morphology",
+    "pha_degrading_microbes",
+    "experimental_scale"
+  ],
+  "categorical_levels": {
+    "additive_type_1": [
+      "crosslinker_polymer_modifier",
+      "filler",
+      "not_applicable",
+      "plasticizer",
+      "reinforcement"
+    ],
+    "additive_type_2": [
+      "filler",
+      "not_applicable",
+      "nucleating_agent",
+      "plasticizer"
+    ],
+    "additive_type_3": [
+      "compatibilizer",
+      "crosslinker",
+      "filler",
+      "not_applicable",
+      "reinforcement"
+    ],
+    "additives": [
+      "no",
+      "yes"
+    ],
+    "degradation_condition": [
+      "aerobic",
+      "anaerobic"
+    ],
+    "degradation_environment": [
+      "compost_organic_fertilizer",
+      "laboratory_mineral_media",
+      "marine_aquatic",
+      "soil"
+    ],
+    "degradation_mechanism": [
+      "hydrolysis",
+      "microbial_enzymatic",
+      "other",
+      "surface"
+    ],
+    "experimental_scale": [
+      "lab",
+      "large"
+    ],
+    "pha_degrading_microbes": [
+      "bacteria_dominated",
+      "bacteria_fungi_mixed",
+      "diverse_environmental",
+      "fungi_dominated",
+      "uncategorized"
+    ],
+    "sample_shape_morphology": [
+      "films",
+      "other",
+      "ribbons",
+      "sheets"
+    ]
+  },
+  "descriptive_interval_half_widths": {
+    "0.80": 53.882681316641424,
+    "0.90": 77.78028288264014,
+    "0.95": 85.50717191428235
+  },
+  "endpoint": "degradation-induced weight loss / physical mass-loss trajectory (%)",
+  "features": [
+    "degradation_time_days",
+    "adjusted_hb_ratio_formulation_mol",
+    "adjusted_hv_ratio_formulation_mol",
+    "t_deg",
+    "additive1_percentage_wt",
+    "additive2_percentage_wt",
+    "additive3_percentage_wt",
+    "degradation_condition",
+    "degradation_mechanism",
+    "additives",
+    "degradation_environment",
+    "additive_type_1",
+    "additive_type_2",
+    "additive_type_3",
+    "sample_shape_morphology",
+    "pha_degrading_microbes",
+    "experimental_scale"
+  ],
+  "grouped_cv_macro_study_mae_objective": 27.81102157801946,
+  "interval_evaluation": {
+    "0.80": {
+      "empirical_coverage": 0.9284253578732108,
+      "mean_width": 79.00438994817615,
+      "median_width": 79.76067915555889
+    },
+    "0.90": {
+      "empirical_coverage": 0.9761417859577368,
+      "mean_width": 91.92065079330042,
+      "median_width": 97.01415518198472
+    },
+    "0.95": {
+      "empirical_coverage": 0.9904567143830948,
+      "mean_width": 97.05151882369664,
+      "median_width": 100.0
+    }
+  },
+  "limitations": [
+    "The effective validation sample contains only 16 source studies.",
+    "Leave-one-study-out errors are large and heterogeneous.",
+    "Prediction intervals are often close to the full 0-100% range.",
+    "Inputs outside recorded ranges or categories require caution.",
+    "Predictions are associations from literature-derived data, not causal estimates."
+  ],
+  "model_name": "bounded_monotonic_study_weighted",
+  "monotonic_constraint": {
+    "direction": "increasing",
+    "feature": "degradation_time_days"
+  },
+  "nested_loso_performance": {
+    "macro_curve_mae": 24.15217559047409,
+    "macro_study_mae": 23.5543495445916,
+    "point_mae": 22.061178747043066,
+    "point_r2": 0.1452965158575815,
+    "point_rmse": 30.482867958078305
+  },
+  "not_endpoint": "ultimate biodegradation or mineralization",
+  "numeric_features": [
+    "degradation_time_days",
+    "adjusted_hb_ratio_formulation_mol",
+    "adjusted_hv_ratio_formulation_mol",
+    "t_deg",
+    "additive1_percentage_wt",
+    "additive2_percentage_wt",
+    "additive3_percentage_wt"
+  ],
+  "numeric_ranges": {
+    "additive1_percentage_wt": {
+      "maximum": 70.0,
+      "minimum": 0.0
+    },
+    "additive2_percentage_wt": {
+      "maximum": 50.0,
+      "minimum": 0.0
+    },
+    "additive3_percentage_wt": {
+      "maximum": 20.0,
+      "minimum": 0.0
+    },
+    "adjusted_hb_ratio_formulation_mol": {
+      "maximum": 99.0,
+      "minimum": 28.16
+    },
+    "adjusted_hv_ratio_formulation_mol": {
+      "maximum": 19.0,
+      "minimum": 0.5
+    },
+    "degradation_time_days": {
+      "maximum": 360.0,
+      "minimum": 0.0
+    },
+    "t_deg": {
+      "maximum": 60.0,
+      "minimum": 20.0
+    }
+  },
+  "random_seed": 42,
+  "sample_weighting": "study_balanced",
+  "software": {
+    "numpy": "1.26.4",
+    "optuna": "3.2.0",
+    "pandas": "2.1.4",
+    "python": "3.10.14",
+    "scikit_learn": "1.7.2",
+    "xgboost": "3.0.5"
+  },
+  "target_transform": {
+    "epsilon": 0.001,
+    "limits": [
+      0,
+      100
+    ],
+    "type": "bounded_logit"
+  },
+  "training_curves": 129,
+  "training_rows": 1467,
+  "training_studies": 16
+}