Datasets:

PeterKol
/

llm-questionnaire-protocol-sensitivity

/**
 * Scores an answers array from scoring-key.csv alone. No product code is involved.
 *
 * The key lists, for every item of the four instruments, the scale it belongs to and the five weights
 * (w0..w4) that the answer index 0..4 earns. A scale's score is
 *   round(100 * sum of the weights of the chosen answers / sum of the largest weight of each of its items).
 * `top` is the first scale, in scale_order, that reaches the highest score (an all-zero profile gives the
 * first scale). Reverse-keyed items are simply items whose weights run downwards.
 *
 * Built on 2026-10-05 as a replacement for the product scorer the analysis used up to then; its output was
 * compared with that scorer on every stored human and model answer vector (see README).
 */
import fs from 'fs'

export function loadKey(file) {
  const lines = fs.readFileSync(file, 'utf8').split(/\r?\n/).filter((l) => l.length)
  const head = lines.shift().split(',')
  const col = Object.fromEntries(head.map((h, i) => [h, i]))
  const tests = {}
  for (const line of lines) {
    const f = line.split(',')
    const t = (tests[f[col.test]] ||= { items: [], order: [] })
    if (Number(f[col.item]) !== t.items.length + 1) throw new Error(`${f[col.test]}: item numbers must run 1..n in order, got ${f[col.item]}`)
    const weights = [0, 1, 2, 3, 4].map((k) => Number(f[col[`w${k}`]]))
    if (weights.some((w) => !Number.isFinite(w))) throw new Error(`${f[col.test]} item ${f[col.item]}: weights must be numbers`)
    t.items.push({ scale: f[col.scale], weights })
    t.order[Number(f[col.scale_order])] = f[col.scale]
  }
  for (const [slug, t] of Object.entries(tests)) {
    if (t.order.some((s) => s == null) || t.items.some((it) => !t.order.includes(it.scale))) throw new Error(`${slug}: scale_order is not a clean 0..k-1 numbering`)
  }
  return tests
}

export function scoreFromKey(key, slug, answers) {
  const t = key[slug]
  if (!t) return null
  const raw = Object.fromEntries(t.order.map((s) => [s, { total: 0, max: 0 }]))
  answers.forEach((a, i) => {
    const it = t.items[i]
    if (!it) return
    raw[it.scale].total += it.weights[a] ?? 0
    raw[it.scale].max += Math.max(...it.weights)
  })
  const scores = {}
  let top = t.order[0]
  let topVal = 0
  for (const s of t.order) {
    const { total, max } = raw[s]
    const p = max > 0 ? Math.round((total / max) * 100) : 0
    scores[s] = p
    if (p > topVal) { topVal = p; top = s }
  }
  return { scores, topResult: top }
}

	/**
	* Scores an answers array from scoring-key.csv alone. No product code is involved.
	*
	* The key lists, for every item of the four instruments, the scale it belongs to and the five weights
	* (w0..w4) that the answer index 0..4 earns. A scale's score is
	* round(100 * sum of the weights of the chosen answers / sum of the largest weight of each of its items).
	* `top` is the first scale, in scale_order, that reaches the highest score (an all-zero profile gives the
	* first scale). Reverse-keyed items are simply items whose weights run downwards.
	*
	* Built on 2026-10-05 as a replacement for the product scorer the analysis used up to then; its output was
	* compared with that scorer on every stored human and model answer vector (see README).
	*/
	import fs from 'fs'

	export function loadKey(file) {
	const lines = fs.readFileSync(file, 'utf8').split(/\r?\n/).filter((l) => l.length)
	const head = lines.shift().split(',')
	const col = Object.fromEntries(head.map((h, i) => [h, i]))
	const tests = {}
	for (const line of lines) {
	const f = line.split(',')
	const t = (tests[f[col.test]] \|\|= { items: [], order: [] })
	if (Number(f[col.item]) !== t.items.length + 1) throw new Error(`${f[col.test]}: item numbers must run 1..n in order, got ${f[col.item]}`)
	const weights = [0, 1, 2, 3, 4].map((k) => Number(f[col[`w${k}`]]))
	if (weights.some((w) => !Number.isFinite(w))) throw new Error(`${f[col.test]} item ${f[col.item]}: weights must be numbers`)
	t.items.push({ scale: f[col.scale], weights })
	t.order[Number(f[col.scale_order])] = f[col.scale]
	}
	for (const [slug, t] of Object.entries(tests)) {
	if (t.order.some((s) => s == null) \|\| t.items.some((it) => !t.order.includes(it.scale))) throw new Error(`${slug}: scale_order is not a clean 0..k-1 numbering`)
	}
	return tests
	}

	export function scoreFromKey(key, slug, answers) {
	const t = key[slug]
	if (!t) return null
	const raw = Object.fromEntries(t.order.map((s) => [s, { total: 0, max: 0 }]))
	answers.forEach((a, i) => {
	const it = t.items[i]
	if (!it) return
	raw[it.scale].total += it.weights[a] ?? 0
	raw[it.scale].max += Math.max(...it.weights)
	})
	const scores = {}
	let top = t.order[0]
	let topVal = 0
	for (const s of t.order) {
	const { total, max } = raw[s]
	const p = max > 0 ? Math.round((total / max) * 100) : 0
	scores[s] = p
	if (p > topVal) { topVal = p; top = s }
	}
	return { scores, topResult: top }
	}