Amrita Vishwa Vidyapeetham

Every collected paper, preprint and grant naming this institution, exactly as the source spells it.

Paper2026-09-28Journal of Materials Engineering and PerformanceSourcedOpenAlex, as fetchedOpen the source → citationsLaser powder-bed fusion machines
Machine Learning-Based Wear Analysis of Laser Powder Bed Fusion Produced SS316L Alloy Using Gaussian Process Regression
China University of Mining and TechnologyAmrita Vishwa Vidyapeetham
Fundamental research · No laboratory or pilot wording.From OpenAlex · not yet reviewedDOI

Computed: For each resolved holding: the bottlenecks its companies hold (maker, capacity or part supplier), the ones a filing says they need or sell into, and everything upstream of a held or needed rail through recorded "needs" rows.Computed: Sum of the weights of the holdings that touch a rail, divided by the sum of the weights of all resolved holdings. With no weights given, every holding counts equally.Computed: For each country: the share of portfolio weight on a rail whose every recorded maker operates there, and the share on a rail with at least one recorded maker there. Part suppliers are not makers.Computed: Direct hits: bottlenecks where the failed node is a maker, a part supplier or the location. Makers wholly inside it are lost; makers also operating elsewhere are partly affected; the rest remain. Downstream: every bottleneck that needs a hit one, transitively, through recorded rows. 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Unchecked pages: open rows in the producer-sourcing queue, counted live from the database.Computed: Count of rows in the market-participant directory.Computed: Count of bottlenecks on which this organisation is recorded as a producer, a holder of the capacity, or a supplier of a critical part.Computed: Accepted events that name this organisation, plus (counted separately) accepted events on a bottleneck it holds that do not name it.Computed: Count of policy instruments in the corpus; each one links its official text.Computed: Count of science entries: technologies recorded as able to relieve a named bottleneck.Computed: Accepted events whose date falls within the last N days of today.Computed: Leads in the research sweep’s queue that no person has read yet and that have not expired, counted live from the database.Computed: Waiting: open sweep leads — no reviewer decision, not expired. Oldest: whole days since the earliest open one was found. Drafts ready: waiting leads whose AI draft suggests an event and passed the checks.Computed: Number of distinct country codes on the rows being counted (makers, or rules).Computed: Rules counted by the effect recorded on each: "tightens" slows building, "loosens" speeds it; a rule recorded as both ways is counted in neither.Computed: Rules with at least one proponent: an organisation that asked for it in a document linked on the row.Computed: A judged level on a nine-step scale from "idea with a physical basis" (1) to "in production at scale" (9).Computed: Technologies tracked = science entries; bottlenecks addressed = distinct bottlenecks named as relieved by any entry; reaching production = entries judged 8 or 9; sourced = entries whose readiness cites a source.Computed: Kinds = rows in the capital-kinds list; providers = named funders, each linking its own mandate page; assessed = bottlenecks with a funding judgement; "money is not it" = those judged "not-money".Computed: Open = calls without a resolution; resolved = right + wrong + unclear; overdue = past the resolve-by date and not yet marked; hit rate = right ÷ (right + wrong), published only once enough calls have resolved.Computed: Bottlenecks on that stage of the loop, and how many of them have every producer row sourced.Computed: The highest severity score among the bottlenecks recorded as gates on the loop.Computed: Count of explainer files in content/learn, and of entries in the glossary.Computed: Sum of the squares of each producer’s share of world output (0–1).Computed: Published reserves ÷ annual production, same place, unit and year.Computed: Accepted events in the last 90 days that tighten it, minus those that loosen it. Neutral events count for neither.Computed: One row per (bottleneck, holder) after the screen’s filters; the bottleneck count is the distinct bottlenecks among those rows.Computed: Organisations recorded on a bottleneck (maker, capacity holder or part supplier) whose shares, or a parent’s, trade on an exchange found in the SEC ticker file or OpenFIGI.Computed: Items per stage = papers, preprints and grants collected for the bottleneck whose relevance score is 2 or more, placed on a stage by the rule in lib/science.ts; judgements are counted separately.Computed: Items first collected in the last 7 days whose publication or award date is within the last 30 days.Computed: Items per institution per bottleneck, counting each item once per institution named on it by the source; a company is matched to the directory only when every distinguishing word of both names agrees.Computed: The latest value in a series minus the value before it, divided by the earlier value, same series and unit.Computed: Count of dated values in a series, or of series matching the filters, across the committed corpus and the official statistics fetched on schedule.Computed: Count of postings currently listed on the public job boards Substrata reads, after the page’s filters. By default software and business roles that name no bottleneck are left out; "Every role" puts them back.Computed: A posting is filed under a bottleneck when its title names one of that bottleneck’s terms, or its description names them at least twice (title only for software and business roles); its role family is the first family whose title terms its title names.Computed: For each skill or credential in the published list, the number of open postings whose title or description names any of its terms.Computed: Count of programmes in research/learning-paths.json, each with the official page it was checked on.Computed: A feed is fresh within one scheduled interval plus half an interval (at least 20 minutes) of its last good run, late up to three intervals, stale beyond; failing when its newest failure is newer than its last good run.Computed: Now minus the finish time of the last good run (feeds), or whole UTC days since the date the committed file records it was checked (datasets).Computed: A sweep lead is open while nobody has reviewed it and it was found less than 30 days ago; unreviewed and 30 days or older, it is expired. The review queue is open leads only: late when its oldest has waited more than 7 days, stale past 31.Computed: Position of a country when the countries USGS lists individually are sorted by the same column, largest first; equal values share a rank.Computed: Latest year ÷ the year before − 1, same country, same column of the same table (USGS or EIA).Computed: A country's resources are ordered by its largest share of world output on any production column of each table (e.g. palladium within PGMs).