30:Tced,html`

This notebook matches radionuclide measurements in marine biota with contemporaneous seawater measurements, based on spatial and temporal proximity, to derive concentration ratios (CR = activity in biota / activity in seawater, both in Bq/kg wet weight) for matched pairs.

Datasets

The biota dataset is the curated dataset prepared for the LaMer CRP seafood dose assessment, exported from MARIS: https://maris.iaea.org/home/news/2145. The seawater dataset comprises all available measurements of the same 16 radionuclides exported from the MARIS database in May 2026.

Matching

For each biota record, seawater measurements within a user-defined radius and time window are identified using a three-stage pre-filter followed by precise distance calculation. First, a binary search on sorted latitude narrows candidates to those within the latitudinal extent of the search radius. Second, a longitude range check (adjusted for latitude) removes records outside the longitudinal extent. Third, a day-difference filter removes records outside the time window. Precise distance is then computed for surviving candidates only using the Haversine formula (via turf.js), keeping only those within the specified radius.

Mean seawater activity and propagated uncertainty are computed across all matching records.

Quality Score

A quality score (0–1) combines normalised spatial and temporal proximity using a weighted geometric mean, and can be used to threshold accepted matches. For each matched seawater record i, the quality score is computed as a weighted geometric mean of normalised spatial and temporal proximity:

${tex.block`q_i = \left(1 - \frac{d_i}{r}\right)^{w_s} \cdot \left(1 - \frac{\Delta t_i}{\Delta T + 1}\right)^{w_t}`}

where dᵢ is the distance (km), r is the maximum radius (km), Δtᵢ is the absolute difference in sampling dates (days), ΔT is the maximum time window (days), and w_s and w_t = 1 − w_s are the spatial and temporal weights. The +1 in the denominator ensures boundary matches score just above zero rather than exactly zero.

The reported quality score Q is the arithmetic mean of qᵢ across all N matched seawater records:

${tex.block`Q = \frac{1}{N}\sum_{i=1}^{N} q_i`}

Q ranges from 0 (poor match) to 1 (perfect co-location and co-timing).

Units

Seawater values reported in Bq/m³ are converted to Bq/kg assuming a seawater density of 1.025 kg/L. Measurements in incompatible units (e.g. DELTA/mill, kg/kg) are excluded.

Statistics

CR distributions are assumed lognormal; geometric mean and geometric standard deviation (GSD) are reported alongside arithmetic statistics. Use the controls below to select nuclide, biogroup, matching radius, time window, spatial/temporal weighting, and minimum quality threshold.

To do

Check the consistency of seawater data - filtered or not
Depth filter
Decay correct seawater values to the sampling date of the biota measurement (for completeness)

Controls

`31:T792,crValues.length === 0 ? html`

No matched results for ${selectedNuclide.symbol} / ${selectedBiogroup} with current parameters.

` : crValues.length < 2 ? html`

Only 1 matched CR (${crValues[0].CR.toFixed(3)}) for ${selectedNuclide.symbol} / ${selectedBiogroup} with current parameters — insufficient data for distribution. Widen radius or time window.

` : Plot.plot({ width: width, height: 400, marginLeft: 60, marginTop: 40, x: { label: "log₁₀(CR)" }, y: { label: "Count" }, marks: [ Plot.rectY( crValues, Plot.binX( { y: "count" }, { x: "logCR", thresholds: d3.range( d3.min(crValues, (d) => d.logCR) - crStats.binWidth, d3.max(crValues, (d) => d.logCR) + crStats.binWidth, crStats.binWidth ), fill: "#a8c8e8", stroke: "#2c6fad", strokeWidth: 1 } ) ), Plot.line(crStats.normalCurve, { x: "x", y: "y", stroke: "red", strokeWidth: 2 }), Plot.ruleX([crStats.mean], { stroke: "red", strokeDasharray: "4,4", strokeWidth: 1.5 }), trs422CR != null ? Plot.ruleX([Math.log10(trs422CR)], { stroke: "darkgreen", strokeWidth: 1.5, strokeDasharray: "6,3" }) : null, // Annotation at top of chart Plot.text([{}], { x: () => crStats.curveMin, y: () => crStats.maxCount, text: () => `N = ${crStats.n},\nGM = ${Math.pow(10, crStats.gm).toFixed(2)}, GSD = ${Math.pow( 10, crStats.gstd ).toFixed(2)}\nAM = ${crStats.am.toFixed(2)}, SD = ${crStats.std.toFixed(2)}` + (trs422CR != null ? `\nTRS 422 CR = ${trs422CR}` : ""), fontSize: 12, fill: "black", textAnchor: "start", dx: 20, dy: 20 }) ] }) 32:T54c,Inputs.table(acceptedResults, { // columns: [ // "id", "sample_id", "ref_id", "latitude", "longitude", "begperiod", // "samplabcode", "biogroup", "species_id", "taxonname", // "bodypar_id", "bodypar", "nuclide_id", "nusymbol", // "corr_activity", "corr_uncertainty", // "sw_activity", "sw_uncertainty", "sw_distances", // "sw_coords", "sw_dates", "sw_refs", "sw_activities", // "quality", "N" // ], columns: [ "id", "sample_id", "biogroup", "CR", "CR_uncertainty", "corr_activity", "corr_uncertainty", "sw_activity", "sw_uncertainty", "N", "quality" ], header: { id: "MARIS ID", sample_id: "Sample ID", biogroup: "Biogroup", CR: "CR", CR_uncertainty: "CR unc.", corr_activity: "Biota act. (Bq/kg)", corr_uncertainty: "Biota unc.", sw_activity: "SW act. (Bq/kg)", sw_uncertainty: "SW unc.", N: "N seawater", quality: "Quality" }, format: { id: (d) => d.toLocaleString("en-US", { useGrouping: false }), sample_id: (d) => d.toLocaleString("en-US", { useGrouping: false }), quality: (d) => { const hue = Math.round(d * 120); return htl.html`${d.toFixed(2)}`; } } })33:T5e9,Plot.plot({ projection: "equirectangular", width: width, height: width / 2, marks: [ Plot.geo(topojson.feature(world, world.objects.countries), { fill: "#e8e8e8", stroke: "#ccc" }), Plot.graticule(), Plot.sphere(), // Seawater hexbin always shown Plot.dot(seawaterFiltered, Plot.hexbin( {fill: "count"}, {x: "longitude", y: "latitude", binWidth: hexBinPx} ) ), // Unmatched + below-threshold biota — unfilled showLayers.includes("Unmatched biota") ? Plot.dot( [ ...biotaFiltered.filter(b => !results.some(r => r.id === b.id)), ...rejectedResults ], { x: "longitude", y: "latitude", stroke: "orange", fill: "none", strokeWidth: 1.5, r: 3, title: d => `${d.taxonname}\n${d.begperiod.toISOString().slice(0,10)}\n${d.corr_activity} ${d.nusymbol}` } ) : null, // Accepted matched biota — filled showLayers.includes("Matched biota") ? Plot.dot(acceptedResults, { x: "longitude", y: "latitude", fill: "orange", stroke: "darkorange", strokeWidth: 1, fillOpacity: 0.9, r: 3, title: d => `${d.taxonname}\n${d.begperiod.toISOString().slice(0,10)}\n${d.corr_activity} ${d.nusymbol}\nQuality: ${(d.quality * 100).toFixed(1)}%` }) : null ].filter(Boolean), color: { scheme: "blues", legend: true, label: "Number of seawater measurements", type: "log" } })34:T5ec,Plot.plot({ width: width, height: 400, marginLeft: 60, //x: { label: "Year", tickFormat: d => d.getFullYear() }, x: { label: "Year", tickFormat: d3.timeFormat("%Y") }, y: { label: `Activity (Bq/kg) — ${selectedNuclide.symbol}`, type: "log" }, marks: [ // Seawater hexbin Plot.dot(seawaterFiltered, Plot.hexbin( {fill: "count"}, {x: d => d.begperiod, y: d => Number(d.activity), binWidth: hexBinPx} ) ), // Unmatched biota — unfilled showLayers.includes("Unmatched biota") ? Plot.dot( [ ...biotaFiltered.filter(b => !results.some(r => r.id === b.id)), ...rejectedResults ], { x: "begperiod", y: "corr_activity", stroke: "orange", fill: "none", strokeWidth: 1.5, r: 3, title: d => `${d.taxonname}\n${d.begperiod.toISOString().slice(0,10)}\n${d.corr_activity} ${d.nusymbol}` } ) : null, // Matched biota — filled showLayers.includes("Matched biota") ? Plot.dot(acceptedResults, { x: "begperiod", y: "corr_activity", fill: "orange", stroke: "darkorange", strokeWidth: 1, fillOpacity: 0.9, r: 3, title: d => `${d.taxonname}\n${d.begperiod.toISOString().slice(0,10)}\n${d.corr_activity} ${d.nusymbol}\nQuality: ${(d.quality * 100).toFixed(1)}%` }) : null ].filter(Boolean), color: { scheme: "blues", legend: true, label: "Number of seawater measurements", type: "log" } })35:T909,allResults = { const combinations = []; for (const nuclide of nuclides) { const swSubset = seawaterNormalised.filter( (d) => d.nuclide_id === nuclide.id ); const swSorted = [...swSubset].sort((a, b) => a.latitude - b.latitude); const biogroups = [ ...new Set(biotaData.map((d) => d.biogroup).filter(Boolean)) ].sort(); for (const biogroup of biogroups) { const biotaSubset = biotaData .filter((d) => d.nuclide_id === nuclide.id) .filter((d) => d.biogroup === biogroup); if (biotaSubset.length === 0) continue; const matched = matchRecords( biotaSubset, swSorted, params.radiusKm, params.timeWindow, spatialWeight ); const accepted = matched.filter((r) => r.quality >= minQuality); const crVals = accepted.filter((r) => r.CR != null && r.CR > 0); if (crVals.length === 0) { combinations.push({ nuclide: nuclide.symbol, biogroup, N: 0, gm: null, gsd: null, am: null, sd: null, trs422: null }); continue; } if (crVals.length === 1) { const trs = trs422Data.find( (d) => d.nuclide === nuclide.symbol && d.biogroup === biogroupToTRS422.get(biogroup) )?.CR ?? null; combinations.push({ nuclide: nuclide.symbol, biogroup, N: 1, gm: crVals[0].CR, gsd: null, am: crVals[0].CR, sd: null, trs422: trs }); continue; } const logVals = crVals.map((d) => Math.log10(d.CR)); const gm = Math.pow(10, d3.mean(logVals)); const gsd = Math.pow(10, d3.deviation(logVals)); const am = d3.mean(crVals, (d) => d.CR); const sd = d3.deviation(crVals, (d) => d.CR); const trs = trs422Data.find( (d) => d.nuclide === nuclide.symbol && d.biogroup === biogroupToTRS422.get(biogroup) )?.CR ?? null; combinations.push({ nuclide: nuclide.symbol, biogroup, N: crVals.length, gm, gsd, am, sd, trs422: trs }); } } return combinations; }36:T12bf,function matchRecords( biotaRecords, seawaterSorted, radiusKm, timeWindow, spatialWeight = 0.5 ) { const temporalWeight = 1 - spatialWeight; const results = []; for (const b of biotaRecords) { const bTime = b.begperiod.getTime(); const bbox = boundingBox(b.latitude, b.longitude, radiusKm); const bPoint = turf.point([b.longitude, b.latitude]); const lo = bisectLeft(seawaterSorted, bbox.minLat); const hi = bisectRight(seawaterSorted, bbox.maxLat); const latCandidates = seawaterSorted.slice(lo, hi); const lonCandidates = latCandidates.filter( (s) => s.longitude >= bbox.minLon && s.longitude <= bbox.maxLon ); const dayCandidates = lonCandidates.filter((s) => { const diffDays = Math.abs(s.begperiod.getTime() - bTime) / (1000 * 60 * 60 * 24); return diffDays <= timeWindow; }); // Compute distance and time diff for each candidate const matchesWithMeta = dayCandidates .map((s) => { const sPoint = turf.point([s.longitude, s.latitude]); const distKm = turf.distance(bPoint, sPoint, { units: "kilometers" }); const diffDays = Math.abs(s.begperiod.getTime() - bTime) / (1000 * 60 * 60 * 24); return { ...s, distKm, diffDays }; }) .filter((s) => s.distKm <= radiusKm); const validMatches = matchesWithMeta.filter( (s) => s.activity != null && s.activity !== "NULL" && !isNaN(Number(s.activity)) ); if (validMatches.length === 0) continue; const N = validMatches.length; const meanActivity = validMatches.reduce((sum, s) => sum + Number(s.activity), 0) / N; const validUncert = validMatches.filter( (s) => s.uncertaint != null && s.uncertaint !== "NULL" && !isNaN(Number(s.uncertaint)) ); const propUncertainty = validUncert.length > 0 ? Math.sqrt( validUncert.reduce((sum, s) => sum + Number(s.uncertaint) ** 2, 0) ) / N : null; // Quality score per match const qualities = validMatches.map((s) => { const spatial = radiusKm > 0 ? 1 - s.distKm / radiusKm : 1; const temporal = timeWindow > 0 ? 1 - s.diffDays / (timeWindow + 1) : 1; // const temporal = timeWindow > 0 ? 1 - s.yearDiff / timeWindow : 1; // Weighted geometric mean return ( Math.pow(spatial, spatialWeight) * Math.pow(temporal, temporalWeight) ); }); const meanQuality = qualities.reduce((sum, q) => sum + q, 0) / N; const swCoords = validMatches .map((s) => `(${s.latitude.toFixed(3)}, ${s.longitude.toFixed(3)})`) .join(", "); const swDates = validMatches .map((s) => s.begperiod.toISOString().slice(0, 10)) .join(", "); const swRefs = validMatches.map((s) => s.ref_id).join(", "); const swActivities = validMatches .map((s) => { const act = Number(s.activity).toFixed(4); const unc = s.uncertaint != null && s.uncertaint !== "NULL" && !isNaN(Number(s.uncertaint)) ? ` ± ${Number(s.uncertaint).toFixed(4)}` : ""; return `${act}${unc}`; }) .join(", "); const swDistances = validMatches .map((s) => `${s.distKm.toFixed(3)} km`) .join(", "); // Concentration ratio const CR = b.corr_activity != null && !isNaN(Number(b.corr_activity)) && meanActivity > 0 ? Number(b.corr_activity) / meanActivity : null; // Propagated uncertainty const CR_uncertainty = CR != null && b.corr_uncertainty != null && !isNaN(Number(b.corr_uncertainty)) && Number(b.corr_activity) > 0 && propUncertainty != null && meanActivity > 0 ? CR * Math.sqrt( Math.pow(Number(b.corr_uncertainty) / Number(b.corr_activity), 2) + Math.pow(propUncertainty / meanActivity, 2) ) : null; results.push({ id: b.id, sample_id: b.sample_id, ref_id: b.ref_id, latitude: b.latitude, longitude: b.longitude, begperiod: b.begperiod, samplabcode: b.samplabcode, biogroup: b.biogroup, species_id: b.species_id, taxonname: b.taxonname, bodypar_id: b.bodypar_id, bodypar: b.bodypar, nuclide_id: b.nuclide_id, nusymbol: b.nusymbol, corr_activity: b.corr_activity, corr_uncertainty: b.corr_uncertainty, sw_activity: meanActivity, sw_uncertainty: propUncertainty, sw_coords: swCoords, sw_dates: swDates, sw_refs: swRefs, sw_activities: swActivities, sw_distances: swDistances, quality: meanQuality, N, CR, CR_uncertainty }); } return results; }37:[{"id":"314bb7ee91b0dd38b8cf16dea63e6b988eaaa666fd6d3dbe41a51f16e4067df126ed097b11135d814a612ec064817caa889ec6af427b4306b958e619c2dd7f91","href":"https://static.observableusercontent.com/files/314bb7ee91b0dd38b8cf16dea63e6b988eaaa666fd6d3dbe41a51f16e4067df126ed097b11135d814a612ec064817caa889ec6af427b4306b958e619c2dd7f91","name":"2024-05-13 LaMer marine biota dataset.xlsx","type":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","lastModified":1779551150864.29,"size":5653302},{"id":"ee9410987f4003fe8ef9c4fbb30feeb6dba2200644e23470a1fc7838861de8ee1934bcba6af10a3000bf4092358a17911cccb2ac988cc72994f59a2c27b8db8e","href":"https://static.observableusercontent.com/files/ee9410987f4003fe8ef9c4fbb30feeb6dba2200644e23470a1fc7838861de8ee1934bcba6af10a3000bf4092358a17911cccb2ac988cc72994f59a2c27b8db8e","name":"IAEA_TRS_422_CRs.csv","type":"text/csv","lastModified":1779652772326.048,"size":5677},{"id":"0a7588f4e6264e6e8c5dedfed8a19528963670cad43b2dfc992f1a26850fe8801681b1d7ab295da8a27cf3380b647d36e3b354e8c681b9518e07ca1ba44b3201","href":"https://static.observableusercontent.com/files/0a7588f4e6264e6e8c5dedfed8a19528963670cad43b2dfc992f1a26850fe8801681b1d7ab295da8a27cf3380b647d36e3b354e8c681b9518e07ca1ba44b3201","name":"2026-05-23 MARIS all seawater data import@3.xlsx","type":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","lastModified":1779554058498.145,"size":17032209}] 2e:{"title":"IAEA MARIS Marine Biota–Seawater Concentration Ratio Calculator","cells":[{"id":265,"value":"# IAEA MARIS Marine Biota–Seawater Concentration Ratio Calculator","pinned":false,"hidden":false,"mode":"md"},{"id":275,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":43,"value":"viewof selectedNuclide = Inputs.select(nuclides, {\n label: \"Nuclide\",\n format: d => d.symbol,\n value: nuclides.find(d => d.symbol === \"Cs-137\") // sensible default\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":86,"value":"viewof selectedBiogroup = Inputs.select(\n [...new Set(biotaData.map(d => d.biogroup).filter(Boolean)).values()].sort(),\n {label: \"Biogroup\", value: \"All\"}\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":58,"value":"viewof params = Inputs.form({\n radiusKm: Inputs.range([0.1, 500], {value: 10, step: 0.1, label: \"Radius (km)\"}),\n timeWindow: Inputs.range([0, 3650], {value: 365, step: 1, label: \"Time window (± days)\"})\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":126,"value":"viewof spatialWeight = Inputs.range([0, 1], {\n value: 0.5, step: 0.1,\n label: \"Spatial weight (0 = time only, 1 = space only)\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":162,"value":"viewof minQuality = Inputs.range([0, 1], {\n value: 0,\n step: 0.01,\n label: \"Minimum quality\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":403,"value":"The following chart shows the distribution of the CRs calculated from the matched biota and seawater measurements for the parameters selected above for radius, time window and quality. ","pinned":false,"hidden":false,"mode":"md"},{"id":226,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":69,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":114,"value":"viewof hexBinPx = Inputs.range([5, 50], {value: 10, step: 1, label: \"Hex bin size (px)\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":119,"value":"viewof showLayers = Inputs.checkbox(\n [\"Matched biota\", \"Unmatched biota\"],\n {value: [\"Matched biota\", \"Unmatched biota\"], label: \"Show layers\"}\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":95,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":309,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":331,"value":"The following chart is included for QA purposes, to help assess the consistency of seawater data from different sources, specifcally regarding filtering of the sample prior to analysis. Also regarding the different fractions:\n- Filtrate (Y) → dissolved fraction — what passes through, typically a 0.45 μm or 0.2 μm membrane\n- Unfiltered (N) → total (dissolved + particulate)\n- The particulate fraction itself (residue/retentate) though this is usually inferred as the difference between total and dissolved ","pinned":false,"hidden":false,"mode":"md"},{"id":188,"value":"Plot.plot({\n width: width,\n height: 300,\n marginLeft: 60,\n x: {\n type: \"log\",\n label: \"Activity (Bq/kg)\",\n ticks: 10,\n tickFormat: d => {\n const exp = Math.log10(d);\n if (Number.isInteger(exp)) return `1e${exp}`;\n return \"\";\n }\n },\n y: {label: \"Filtered?\"},\n color: {legend: true, label: \"Filtered\"},\n marks: [\n Plot.boxX(seawaterFiltered.filter(d => \n d.activity != null && d.activity !== \"NULL\" && \n !isNaN(Number(d.activity)) && Number(d.activity) > 0\n ), {\n x: d => Number(d.activity),\n y: d => d.filtered,\n fill: \"filtered\",\n fillOpacity: 0.7\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":460,"value":"## All results","pinned":false,"hidden":false,"mode":"md"},{"id":456,"value":"The following table shows all CRs calculated from the matched biota and seawater measurements for the parameters selected above for radius, time window and quality","pinned":false,"hidden":false,"mode":"md"},{"id":431,"value":"Inputs.table(allResults.map(d => ({\n ...d,\n gm: d.gm ?? \"—\",\n gsd: d.gsd ?? \"—\",\n am: d.am ?? \"—\",\n sd: d.sd ?? \"—\",\n trs422: d.trs422 ?? \"—\"\n})), {\n header: {\n nuclide: \"Nuclide\",\n biogroup: \"Biogroup\",\n N: \"N\",\n gm: \"GM\",\n gsd: \"GSD\",\n am: \"AM\",\n sd: \"SD\",\n trs422: \"TRS 422\"\n },\n format: {\n gm: d => typeof d === \"number\" ? d.toFixed(0) : d,\n gsd: d => typeof d === \"number\" ? d.toFixed(1) : d,\n am: d => typeof d === \"number\" ? d.toFixed(0) : d,\n sd: d => typeof d === \"number\" ? d.toFixed(0) : d,\n trs422: d => typeof d === \"number\" ? d.toFixed(0) : d\n },\n sort: \"nuclide\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":429,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":167,"value":"acceptedResults = results.filter((r) => r.quality >= minQuality)","pinned":true,"hidden":false,"mode":"ojs"},{"id":169,"value":"rejectedResults = results.filter(r => r.quality < minQuality)","pinned":true,"hidden":false,"mode":"ojs"},{"id":106,"value":"pixelsPerKm = width / (360 * 111.32 * Math.cos(20 * Math.PI / 180))","pinned":true,"hidden":false,"mode":"ojs"},{"id":109,"value":"hexBinWidth = params.radiusKm * pixelsPerKm * 2","pinned":true,"hidden":false,"mode":"ojs"},{"id":41,"value":"nuclides = [...new Map(\n biotaData.map(d => [d.nuclide_id, d.nusymbol])\n).entries()]\n .map(([id, symbol]) => ({id, symbol}))\n .filter(d => new Set(seawaterData.map(s => s.nuclide_id)).has(d.id))\n .sort((a, b) => a.symbol.localeCompare(b.symbol))","pinned":false,"hidden":false,"mode":"ojs"},{"id":47,"value":"biotaFiltered = biotaData\n .filter(d => d.nuclide_id === selectedNuclide.id)\n .filter(d => selectedBiogroup === \"All\" || d.biogroup === selectedBiogroup)\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":49,"value":"seawaterFiltered = seawaterNormalised\n .filter((d) => d.nuclide_id === selectedNuclide.id)\n .filter((d) => VALID_UNITS.has(d.unit))","pinned":false,"hidden":false,"mode":"ojs"},{"id":73,"value":"seawaterSorted = [...seawaterFiltered].sort((a, b) => a.latitude - b.latitude)","pinned":true,"hidden":false,"mode":"ojs"},{"id":193,"value":"VALID_UNITS = new Set([\"Bq/kg\", \"Bq/m3\"])","pinned":true,"hidden":false,"mode":"ojs"},{"id":51,"value":"function boundingBox(lat, lon, radiusKm) {\n const KM_PER_DEG_LAT = 111.32;\n const latDelta = radiusKm / KM_PER_DEG_LAT;\n const lonDelta = radiusKm / (KM_PER_DEG_LAT * Math.cos(lat * Math.PI / 180));\n return {\n minLat: lat - latDelta, maxLat: lat + latDelta,\n minLon: lon - lonDelta, maxLon: lon + lonDelta\n };\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":53,"value":"function bisectLeft(arr, val) {\n let lo = 0,\n hi = arr.length;\n while (lo < hi) {\n const mid = (lo + hi) >> 1;\n if (arr[mid].latitude < val) lo = mid + 1;\n else hi = mid;\n }\n return lo;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":55,"value":"function bisectRight(arr, val) {\n let lo = 0,\n hi = arr.length;\n while (lo < hi) {\n const mid = (lo + hi) >> 1;\n if (arr[mid].latitude <= val) lo = mid + 1;\n else hi = mid;\n }\n return lo;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":65,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":67,"value":"results = matchRecords(biotaFiltered, seawaterSorted, params.radiusKm, params.timeWindow, spatialWeight)","pinned":false,"hidden":false,"mode":"ojs"},{"id":415,"value":"### Imports","pinned":false,"hidden":false,"mode":"md"},{"id":60,"value":"turf = require(\"@turf/turf\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":90,"value":"world = fetch(\"https://cdn.jsdelivr.net/npm/world-atlas@2/countries-110m.json\").then(r => r.json())","pinned":true,"hidden":false,"mode":"ojs"},{"id":92,"value":"topojson = require(\"topojson-client\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":417,"value":"### Data imports","pinned":false,"hidden":false,"mode":"md"},{"id":17,"value":"biotaData = await FileAttachment(\"2024-05-13 LaMer marine biota dataset.xlsx\")\n .xlsx()\n .then(wb => wb.sheet(\"LaMer marine biota dataset\", {headers: true}))","pinned":true,"hidden":false,"mode":"ojs"},{"id":26,"value":"seawaterData = await FileAttachment(\"2026-05-23 MARIS all seawater data import@3.xlsx\")\n .xlsx()\n .then(wb => wb.sheet(\"MARIS all seawater data\", {headers: true}))","pinned":true,"hidden":false,"mode":"ojs"},{"id":190,"value":"seawaterNormalised = seawaterData.map(d => {\n if (d.unit === \"Bq/m3\") {\n return {\n ...d,\n activity: d.activity != null && !isNaN(Number(d.activity)) \n ? Number(d.activity) / 1025 \n : d.activity,\n uncertaint: d.uncertaint != null && d.uncertaint !== \"NULL\" && !isNaN(Number(d.uncertaint))\n ? Number(d.uncertaint) / 1025\n : d.uncertaint,\n unit: \"Bq/kg\",\n unit_id: d.unit_id // keep original unit_id for reference\n };\n }\n return d;\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":31,"value":"For seawater export: \n```sql\nSELECT sample_id, ref_id, latitude, longitude, begperiod, totdepth, sampdepth, station, \n samplabcode, nusymbol, nuclide_id, salinity, filtered, filtpore, detection, activity, \n uncertaint, unit_id, unit, id \nFROM [MARIS_QA].[dbo].[exportsample]\nWHERE samptype_id = 1 \n AND shapetype_id = 1 \n AND nuclide_id IN (22,3,33,41,47,68,77,53,54,12,15,57,106,59,62,64) \n AND detection = '='\n```","pinned":false,"hidden":false,"mode":"md"},{"id":319,"value":"### CR calculations","pinned":false,"hidden":false,"mode":"md"},{"id":220,"value":"// Compute log10 CR values for matched results\ncrValues = acceptedResults\n .filter(r => r.CR != null && r.CR > 0)\n .map(r => ({...r, logCR: Math.log10(r.CR)}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":229,"value":"crStats = {\n if (crValues.length === 0) return null;\n if (crValues.length < 2) return null; // need at least 2 for SD\n const vals = crValues.map((d) => d.CR);\n const am = d3.mean(vals);\n const std = d3.deviation(vals);\n const valsLog = crValues.map((d) => d.logCR);\n const gm = d3.mean(valsLog);\n const gstd = d3.deviation(valsLog);\n const n = valsLog.length;\n const binWidth = 0.2;\n const xMin = gm - 4 * gstd;\n const xMax = gm + 4 * gstd;\n const normalCurve = d3.range(xMin, xMax, 0.05).map((x) => ({\n x,\n y:\n ((n * binWidth) / (gstd * Math.sqrt(2 * Math.PI))) *\n Math.exp(-0.5 * Math.pow((x - gm) / gstd, 2))\n }));\n const curveMin = xMin;\n const maxCount = d3.max(\n d3.bin().thresholds(d3.range(xMin, xMax, binWidth))(valsLog),\n (b) => b.length\n );\n return { gm, gstd, am, std, n, binWidth, normalCurve, maxCount, curveMin };\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":325,"value":"### IAEA TRS 422 data \nhttps://www-pub.iaea.org/MTCD/Publications/PDF/TRS422_web.pdf","pinned":false,"hidden":false,"mode":"md"},{"id":289,"value":"trs422Data = await FileAttachment(\"IAEA_TRS_422_CRs.csv\").csv({typed: true})","pinned":true,"hidden":false,"mode":"ojs"},{"id":297,"value":"biogroupToTRS422 = new Map([\n [\"Fish\", \"Fish\"],\n [\"Crustaceans\", \"Crustaceans\"],\n [\"Bivalves\", \"Molluscs\"],\n [\"Gastropods\", \"Molluscs\"],\n [\"Cephalopods\", \"Cephalopods\"],\n [\"Seaweeds and plants\", \"Macroalgae\"],\n])","pinned":false,"hidden":false,"mode":"ojs"},{"id":300,"value":"trs422CR = trs422Data.find(d =>\n d.nuclide === selectedNuclide.symbol &&\n d.biogroup === biogroupToTRS422.get(selectedBiogroup)\n)?.CR ?? null","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W37","stdlib":"1","titling":"auto"}