Privacy Policy

SciViD

SciViD Privacy Policy

Effective date: 28 October 2026

This Privacy Policy explains how SciViD Pty Ltd collects, uses, discloses and protects personal information when you use www.scivid.ai, submit work to SciViD or take part in a SciViD workshop. We handle personal information in line with the Australian Privacy Principles in the Privacy Act 1988 (Cth). If the EU or UK General Data Protection Regulation applies to you, you also have the rights described in section 12.

1. Who we are

SciViD is operated by SciViD Pty Ltd (ACN 686 725 913, ABN 85 686 725 913), Brisbane, Queensland, Australia (“SciViD”, “we”, “us”). SciViD Pty Ltd is responsible for the personal information described here. Privacy inquiries: editor@scivid.net.

2. Information we collect

Contact and account details: name, email address, school or institution, country, role (student, teacher, mentor or researcher), and login details if you create an account.
Submission materials: manuscript, video abstract, figures, data, code, interactive lab files, contribution statement and AI-use statement. A video abstract contains the presenter’s voice and, only if the authors choose, their image.
Consent and sign-off records: for authors under 18, the names and contact details of the student and of a parent or guardian, their consent and its date. For Emerging Scholars items, the name and role of the supervising teacher or mentor and their sign-off.
Payments, where applicable (for example for workshops): billing name, email address, address where needed for an invoice, the item paid for and payment status. Card and bank details are handled by the payment provider; we do not store full card numbers.
Communications: emails and messages you send us, checklist feedback and workshop requests.
Technical and usage data: IP address, browser and device type, pages visited, referring pages and cookie identifiers, collected by our website platform and analytics tools.

We do not ask for sensitive information such as health information. Authors must not submit information that identifies research participants.

3. How we use it

To receive, check and post submissions, and to manage versions, corrections and withdrawals.
To contact authors, parents or guardians, and mentors about a submission.
To deposit an item with Zenodo to obtain a DOI, only when the authors and, for authors under 18, a parent or guardian have agreed.
To issue invoices and keep financial records, where payments apply.
To run, secure and improve the website, including understanding how pages are used.
To send news about SciViD, only if you have opted in. You can unsubscribe at any time.
To comply with the law.

4. What is published

A posted item is public. It shows the authors’ names and school or institution, the names and roles of teachers or mentors in the acknowledgements, the manuscript, the video abstract and any interactive lab. We never publish any author’s email address, phone number or home address.

For authors under 18:

names and school are published only with a parent’s or guardian’s consent;
we do not publish photographs of them;
their faces appear in a video abstract only with that consent.

Because posted items are public and may be openly licensed, others may copy or link to them (see section 9).

5. AI tools

We may use AI tools to help with language editing and formatting checks. AI tools do not decide whether an item is posted. We use services and settings under which the content we enter is not used to train the provider’s models. We do not enter the contact details of authors under 18 into AI tools.

6. Service providers and overseas disclosure

We share personal information only with service providers that help us run SciViD, and only as far as needed:

Wix.com, our website platform (hosting, forms, member accounts and site statistics);
our email service provider;
payment providers, where payments apply;
Zenodo, operated by CERN, when a DOI is requested with consent;
video hosting services, where a video abstract is hosted outside our website platform.

These providers may store information outside Australia, including in the United States, the European Union and Switzerland. We also disclose information where the law requires it. We do not sell personal information.

7. Cookies and analytics

Our website platform sets cookies that the site needs to work, for example for security and logins. Where enabled, it also sets cookies that measure how the site is used. Where the law requires consent, we ask for it through a cookie banner, and you can change your choice at any time. You can also block or delete cookies in your browser, although some features may then not work.

8. Legal bases (EU and UK)

Where the GDPR or UK GDPR applies, we rely on:

performance of a contract: to process submissions and provide the services you request;
consent: for newsletters, non-essential cookies, Zenodo deposits and the participation of authors under 18;
legitimate interests: to keep the site secure, maintain the public record of posted items and improve the site;
legal obligation: for example, tax records.

9. How long we keep information

Posted items stay public as part of the SciViD record, including earlier versions. If an item is withdrawn, a withdrawal notice remains. At the request of an author, or of a parent or guardian of an author under 18, we remove the author’s personal details from that notice. For an author under 18, a parent or guardian may instead ask us to remove the item completely, including the notice.
Unposted submissions: deleted within 12 months after the final decision or withdrawal.
Consent and sign-off records: kept while the item is posted and for 2 years after it is removed.
Invoices and payment records: 5 years, as required by Australian tax law.
Account details: until you close your account.
Correspondence: up to 3 years after our last contact, unless it relates to a posted item.
Analytics data: according to the retention settings of our analytics tools.

We cannot remove copies of an openly licensed item that others have already made. Zenodo records are intended to be permanent (see our Terms and Conditions).

10. Children and young people

SciViD is not intended for children under 13, and we do not knowingly collect their personal information. Students aged 13 to 17 may submit work only with the written consent of a parent or guardian. A parent or guardian can ask us at any time to withdraw the student’s item and remove the student’s personal details. If we learn that we hold information about a child under 13, or about a student under 18 without the required consent, we will delete it.

11. Security

We take reasonable steps to protect personal information, including access controls and encrypted (HTTPS) connections. No online service is completely secure. If a data breach is likely to cause serious harm, we will notify affected people and regulators where the law requires it.

12. Your rights

You can ask to access or correct your personal information, ask us to delete it, withdraw your consent or opt out of emails. If the GDPR or UK GDPR applies to you, you can also ask us to restrict or object to processing and to provide your data in a portable format. Email editor@scivid.net. We respond within 30 days and may first need to confirm your identity.

13. Complaints

Please contact us first at editor@scivid.net. If you are not satisfied with our response, you can contact the Office of the Australian Information Commissioner (www.oaic.gov.au) or, in the EU or UK, your local data protection authority.

14. Changes to this policy

We may update this policy. We will post the new version on this page with a new effective date and, for significant changes, notify registered users by email. Earlier versions are available on request.

SciViD Pty Ltd · Brisbane, Queensland, Australia · editor@scivid.net

Label	Meaning	Minimum evidence
Benchmarked	The method reproduces an independent reference, and the result is converged	Benchmark comparison, convergence or repeatability test, documented source data
Simplified estimate	An order-of-magnitude or reduced-model result with stated assumptions	Assumptions listed, validity range stated, no claim beyond that range
Conceptual	An illustration of an idea, mechanism or scenario	Clearly marked as illustrative; not used as evidence

Mistake	How to detect it	How to handle it
Model used outside its regime (e.g., continuum flow where the gas is rarefied, inertia included at very low Reynolds number, Brownian motion neglected for sub-micrometer particles)	Compute the relevant dimensionless numbers (Reynolds, Knudsen, Péclet, Biot) for your parameters	State the regime explicitly; choose a model valid in it; cite the source that defines the validity range
Unit and dimension errors (mixing µm and m, °C and K, per-minute and per-second rates)	Check that every equation is dimensionally consistent; run one case by hand	Work in SI units internally; convert only for display; label every axis and value with units
Wrong or unstated boundary and initial conditions	Ask: what happens at each wall, inlet, outlet and at t = 0?	Write them out in the methods; justify each against the physical system
No comparison with a known solution	Ask: has this code ever reproduced a result I did not produce myself?	Reproduce an analytical limit or a published benchmark first; show the comparison
No convergence test	Results change when the mesh, time step or sample size is refined	Refine at least twice; report the change in the key quantity; use the converged setting
AI-generated code accepted without checking	The author cannot explain each line or each parameter	Read and comment the code; test it on a case with a known answer; record what the AI tool produced in the Claim & AI-use log
Parameter values without a source	A value appears in a table or narration with no reference	Give a reference, a measurement or an explicit assumption for every parameter
Too few samples for stochastic results	Brownian or Monte Carlo results vary noticeably between runs	Run multiple independent realizations; report the mean and spread

Mistake	Example	Correct handling
Overclaiming	“This device could revolutionize drug delivery” from a single simulation	State what was shown, under which assumptions, and what remains untested
Correlation presented as mechanism	Two quantities change together, so one is said to cause the other	Say “is associated with”; propose the mechanism as a hypothesis and state how to test it
Estimate presented as validated	An order-of-magnitude force estimate narrated as a measured result	Use the correct status label in the text, on screen and in the narration
Missing uncertainty	A single number with no error bar or range	Report the spread across runs, parameter sensitivity, or the range of validity
Selected parameters	Only the parameter set that “works” is shown	Show the parameter sweep, including cases where the effect disappears
Novelty not checked	“For the first time” without a literature search	Search the literature; cite prior work; describe precisely what is new
Extrapolation beyond the model	A result at the micrometer scale is narrated as applying to the human body	Restrict claims to the scale and conditions modeled

Mistake	Why it matters	Correct handling
Conceptual animation mistaken for evidence	A 3D render or generative-video shot looks like a result	Mark such shots on screen as “Conceptual illustration”; keep data-derived visuals visually distinct
Generative video showing physically impossible behavior	AI video tools do not obey physics; motion, scale and timing may be wrong	Use generative footage only for non-evidentiary context; never to show a result
Plots without units, scale bars or error bars	The viewer cannot judge magnitude or reliability	Label axes with quantity and SI unit; add scale bars to images; show uncertainty
Misleading color maps	Rainbow-type maps create false boundaries and are hard to read for colorblind viewers	Use perceptually uniform maps (e.g., viridis, cividis); show the color bar with units
Truncated or inconsistent axes	Small differences look large; panels cannot be compared	Start axes at zero where magnitudes are compared; use the same scale across panels
Narration diverging from the data	The voiceover states a value or trend the figure does not show	Script the narration from the results file; check every number spoken against the source
Time and length scales not shown	Slowed or accelerated motion, or magnified objects, mislead viewers	Display time stamps, playback speed and scale bars
Too much on screen at once	Viewers cannot follow equations, plots and narration simultaneously	One idea per scene; give equations time to be read

Topic	Resource	What it gives you
Reproducible computation	Sandve et al. (2013), Ten Simple Rules for Reproducible Computational Research, PLOS Comput. Biol. 9, e1003285	Practical rules: track how each result was produced, record versions and random seeds, store the raw data behind plots
Figures	Rougier, Droettboom and Bourne (2014), Ten Simple Rules for Better Figures, PLOS Comput. Biol. 10, e1003833	Designing figures for a given audience, message and medium
Color maps	Crameri, Shephard and Heron (2020), The misuse of colour in science communication, Nat. Commun. 11, 5444	Why rainbow and red–green maps distort data; how to choose accessible, perceptually uniform maps
Units	BIPM, The International System of Units (SI Brochure, 9th edition)	Authoritative definitions and rules for writing SI units and quantities
AI and authorship	COPE position statement: Authorship and AI tools	Why AI tools cannot be authors and what authors must disclose
Coding skills	Software Carpentry lessons	Free introductory lessons on the Unix shell, Git, and Python or R
Archiving data and code	Zenodo	A free general-purpose repository operated by CERN that assigns a DOI to each deposit

SciViD

Privacy Policy

Common Mistakes in Video Preprints

1. Purpose and scope

Result status labels

2. Common mistakes in modeling and computation

3. Common mistakes in interpretation and claims

4. Common mistakes in visualization and video

5. Less obvious mistakes

6. Integrity, authorship and AI disclosure

7. Pre-submission checklist

Model and computation

Results and claims

Video

Integrity and reproducibility

8. Where to find help