Training Example: QuanTech Inc. – Review the Data, Give Your Score & Compare to the Real AI Evaluation

Industry Context — Common BS Fingerprints in Science, Research & Laboratories
Generic Claims: world-class research, pioneering scientific breakthroughs, advancing knowledge, trusted by leading institutions…
Red Flags: accreditation claims without certificate numbers, no publication record for research claims, unnamed scientists or researchers, breakthrough claims without peer review…
Semantic Drift Patterns: homepage claims cutting-edge but equipment list is dated, claims accredited but no accreditation schedule or scope shown, research claims but no publication list, claims GLP but no regulatory inspection history…
Proof Expectations: accreditation certificate numbers and scope (ISO 17025, GLP), publication list with peer-reviewed journal citations, named principal investigators with verifiable track records, specific equipment list with calibration status…

QuanTech Inc.

(https://quantech.com) 📸 Data Snapshot: June 19, 2026

Analyze the raw signals below. How would a machine score this business’s credibility?

Here are the exact signals captured from up to six pages of the site — the same raw inputs the evaluation engine analyzed. They are grouped by signal type so you can weigh each the way the machine does.

🏗️ Semantic Structure — heading hierarchy & page identity (Info Density · Commodity Fingerprint)
HOMEPAGE Home – QuanTech Inc. (https://quantech.com)
Title

Home – QuanTech Inc.

NAV_REPEATED_BODY Lead/Healthy Homes – QuanTech Inc. (https://quantech.com/lead-healthy-homes/)
Title

Lead/Healthy Homes – QuanTech Inc.

Meta

In 2005-2006, QuanTech conducted the American Healthy Homes Survey for the Department of Housing and Urban Development (HUD) and the Environmental Protection Agency (EPA). The purpose of the survey was to measure the presence of lead, arsenic, allergens and pesticides in housing nationwide. A total of 1,131 homes were surveyed; a random subsample of 500 of those homes were sampled for pesticides. QuanTech continues to provide analytical support to HUD to investigate trends in the data collected. QuanTech has been involved in LBP work for EPA and HUD since the founding of the firm. The Environmental Sciences Group is managed by Dr. Gary Dewalt, who is active in the environmental testing industry. Dr. Dewalt served as project leader for most QuanTech lead-based paint studies involving field and chemical analysis activities, and was the task leader for field and laboratory portions of the EPA/HUD field study: Field Test of Lead-Based Paint Testing Technologies. This study, a joint effort conducted by QuanTech and Midwest Research Institute, was designed by Dr. David Cox, the President of QuanTech. Dr. Cox was also the author of Chapter 4, "Testing for Lead-Based Paint", in the 1990 HUD Guidelines, and of EPA's Model Lead Inspector Course published in 1993. QuanTech was involved in designing and conducting follow-on activities to the Field Test of Lead-Based Paint Testing Technologies, including operation of a testing archive formed from samples collected in the field study. This testing archive is used to develop Performance Characteristic Sheets (PCSs) for XRF testing as directed by the 1995 HUD Guidelines. QuanTech also designed and developed paint film standards for the National Lead Abatement Council (NLAC) in support of the National XRF Operators Registry through a grant funded from HUD. QuanTech produces leaded film standards for XRF and Test Kit applications.

REPEATED_BODY Large Pelagics Survey – QuanTech Inc. (https://quantech.com/lps/)
Title

Large Pelagics Survey – QuanTech Inc.

Meta

QuanTech's Fisheries Research Group conducts the Large Pelagics Survey (LPS) for the US Department of Commerce, National Oceanic and Atmospheric Administration, National Marine Fisheries Service, NOAA Fisheries, Office of Science and Technology. Since 1992, the National Marine Fisheries Service has administered the LPS to collect information about the recreational fishery directed at large pelagic species (e.g., tunas, billfishes, swordfish, sharks, wahoo, dolphinfish, and amberjack) in the offshore waters from Maine through Virginia. Participation in this survey is greatly appreciated and is an important step toward fulfilling mandatory reporting requirements as an Highly Migratory Species (HMS) permit holder. The authority to collect LPS data comes from the Atlantic Tunas Convention Act and the Magnuson-Stevens Fishery Conservation and Management Act. The collection of catch and effort information on large pelagics also fulfills U.S. obligations to the International Commission for the Conservation of Atlantic Tunas (ICCAT). The LPS includes two independent, yet complementary, surveys which provide the effort and average catch per trip estimates needed to estimate total catch by species. The Large Pelagics Intercept Survey (LPIS) is a dockside survey of fishing access sites, primarily designed to collect catch data from private and charterboat captains who have just completed fishing trips directed at large pelagic species. LPIS data are used to estimate the average recreational catch per large pelagic boat trip by species. The LPIS involves intensive field interviewing in the coastal areas from Virginia through Maine. In Maine, the LPIS is conducted by State personnel. QuanTech conducts the LPIS from Virginia through New Hampshire. The LPIS involves: Revision and refinement of all field survey instruments and data collection procedures in cooperation with NOAA Fisheries; Creation and maintenance of a sampling frame of large pelagic fishing access sites; Detailed training of field interviewers in the methodology and procedures to be used in the field interviewing process; and, Procedures to verify and enhance the quality of the data collected using comprehensive field management techniques, and in-house SAS data checking programs. To meet the requirement of delivery of LPIS data files to NOAA Fisheries, data collected in the field is sent within 24 hours of interviewing assignment completion and checked for completeness and consistency. Optical Character Recognition (OCR) software is used to capture data from field forms. During data capture each entry on the form is verified by an OCR operator. A SAS dataset meeting NOAA Fisheries' specifications is prepared and delivered to NOAA Fisheries each month. The Large Pelagics Telephone Survey (LPTS) is conducted from QuanTech Headquarters in Rockville, Maryland using a custom-designed Computer Assisted Telephone Interviewing system. The LPTS collects data used to estimate the total number of boat trips on which anglers fished with rod and reel or handline for large pelagic species. For-hire boats are covered by a weekly survey, and private boats are covered by a biweekly survey. The Charter/Headboat LPTS is a survey of charter and headboat fishing for HMS. The Private LPTS covers both commercial fishing by vessels with General category HMS permits, and true recreational fishing by vessels with Angling category HMS permits.

NAV_REPEATED_BODY In-Person Surveys – QuanTech Inc. (https://quantech.com/intercept/)
Title

In-Person Surveys – QuanTech Inc.

Meta

QuanTech specializes in in-person intercept surveys to collect various types of survey data. We have a network of experienced field supervisors that oversee highly trained interviewing staff. Our interviewing staff is trained on how to approach potential respondents in a manner that results in a high level of participation; they are also trained to convert soft refusals into participating respondents. Depending on our clients’ needs we collect the data using two methods; paper survey responses and electronic field data collection. Paper surveys are filled out by our interviewers and sent to QuanTech's headquarters where advanced image capturing software is used to convert handwritten responses into electronic text which is then validated by our office staff. QuanTech is also using cutting edge computer assisted personal interviewing systems to easily collect survey responses in the field. QuanTech employs experienced programming staff to design, develop and program electronic surveys that are deployed to laptops or sunlight readable tablets. Our field staff are trained to use electronic devices to efficiently collect responses from participants. A major benefit of electronic field data collection is the ability to incorporate complex skip rules and error checks that ensure the highest quality data is delivered to our clients in a timely manner.

📝 The Narrative — clean text per page (Info Density · Semantic Coherence)
HOMEPAGE (https://quantech.com) Home – QuanTech Inc.
American Healthy Homes Survey IIDockside InterviewsComputer Assisted Telephone InterviewsElectronic Field Data CollectionLarge Pelagic Biological Survey
QuanTech is Currently Conducting the Following Studies
2026 North Atlantic Striped Bass and Bluefish Recreational Fishing Survey
QuanTech is conducting a mail push to web survey of recreational saltwater anglers on the Atlantic coast from Maine through North Carolina sponsored by the Atlantic States Marine Fisheries Commission (ASMFC). The goal of this survey is to help the ASMFC understand how anglers may be affected by potential changes in fishing conditions. If you were mailed a survey invitation with an access code, click
here to access the survey.
American Healthy Homes Survey II
QuanTech is conducting data analysis for the second American Healthy Homes
Survey (AHHS II) for the U.S. Department of Housing and Urban Development’s
(HUD’s) Office of Lead Hazard Control and Healthy Homes
www.hud.gov/healthyhomes. In AHHS
II, homes are
tested for lead in paint, dust, soil and water; pesticides and mold in dust;
formaldehyde in air; and, safety hazards. QuanTech conducted the survey between
March 2018 and May 2019 in 78 cities and counties in 37 states all over the
U.S. Approximately 800 homes have been randomly selected in these areas to
participate in the survey. QuanTech is currently analyzing the results.
If your home is one of the 800 selected, you will receive an
official letter inviting you to participate and offering you a financial
incentive of $130. Even if you believe your home is free of lead paint or
other hazards, HUD is still interested in testing it because this is the only
way to be sure and to get an accurate count of how many of the tested homes do
have hazards.
More information about AHHS II can be found on
HUD’s website at:
https://www.hud.gov/program_offices/healthy_homes/ahhs_ii
Large Pelagics Survey
The Large Pelagics Survey collects information about the recreational fishery directed at large pelagic species (e.g., tunas, billfishes, swordfish, sharks, wahoo, dolphinfish, and amberjack) in the offshore waters from Maine through Virginia.
More...
Past projects conducted by QuanTech

Interviewer Resources
Clients
NOAA Fisheries
Housing and Urban Development
U.S. Environmental Protection Agency
National Center for Healthy Housing
Maryland Department of Natural Resources
2404 chars
SUB-PAGE (https://quantech.com/lead-healthy-homes/) Lead/Healthy Homes – QuanTech Inc.
Lead
Based Paint and Healthy Homes
In 2005-2006, QuanTech conducted the American Healthy Homes Survey
for the Department of Housing and Urban Development (HUD) and the Environmental
Protection Agency (EPA). The purpose of the survey was to measure the presence
of lead, arsenic, allergens and pesticides in housing nationwide. A total of
1,131 homes were surveyed; a random subsample of 500 of those homes were sampled
for pesticides. QuanTech continues to provide analytical support to HUD to
investigate trends in the data collected.QuanTech is now conducting the second American Healthy Homes
Survey (AHHS II) to collect information on lead in paint, dust, soil and
water; pesticides and mold in dust; formaldehyde in air; and, safety hazards,
in a random sample of 800 homes nationwide. The selected homes are located in
37 different states all over the U.S. and were scientifically selected to
represent all homes in the country. The second survey will update information
on lead, pesticides and mold from the first AHHS, and will provide the first
national estimates of how common lead is in drinking water and how much
formaldehyde is in the air in homes. More information about AHHS II can
be found on HUD’s website at:https://www.hud.gov/program_offices/healthy_homes/ahhs_iiQuanTech has been involved in LBP work for EPA and HUD since the
founding of the firm. The Environmental Sciences Group is managed by Dr. Gary Dewalt, who is active in the environmental testing
industry. Dr. Dewalt served as project leader for most QuanTech lead-based
paint studies involving field and chemical analysis activities, and was the
task leader for field and laboratory portions of the EPA/HUD field study: Field Test of Lead-Based Paint
Testing Technologies. This study, a joint
effort conducted by QuanTech and Midwest Research Institute, was designed
by Dr. David Cox, the President of QuanTech. Dr. Cox was also
the author of Chapter 4, "Testing for Lead-Based Paint", in the 1990
HUD Guidelines, and of EPA's Model Lead Inspector Course published in 1993.QuanTech was involved in designing and conducting follow-on
activities to the Field Test of Lead-Based Paint Testing Technologies, including operation of a testing archive
formed from samples collected in the field study. This testing archive is used
to develop Performance Characteristic Sheets (PCSs) for XRF testing as directed
by the 1995 HUD Guidelines.QuanTech also designed and developed paint film standards for the
National Lead Abatement Council (NLAC) in support of the National XRF Operators
Registry through a grant funded from HUD. QuanTech produces leaded film standards for XRF and Test Kit applications.
Projects
For additional information on healthy homes projects, please see:
American Healthy Homes Survey
Performance Characteristic Sheets for XRF Instruments
The National Center for Healthy Housing Watts to Well Being Survey
2903 chars
SUB-PAGE (https://quantech.com/lps/) Large Pelagics Survey – QuanTech Inc.
QuanTech's Fisheries Research Group conducts the Large Pelagics Survey (LPS) for the US Department of Commerce, National Oceanic and Atmospheric Administration, National Marine Fisheries Service, NOAA Fisheries, Office of Science and Technology.
Since 1992, the National Marine Fisheries Service has administered the LPS to collect information about the recreational fishery directed at large pelagic species (e.g., tunas, billfishes, swordfish, sharks, wahoo, dolphinfish, and amberjack) in the offshore waters from Maine through Virginia. Participation in this survey is greatly appreciated and is an important step toward fulfilling mandatory reporting requirements as an Highly Migratory Species (HMS) permit holder.
The authority to collect LPS data comes from the Atlantic Tunas Convention Act and the Magnuson-Stevens Fishery Conservation and Management Act. The collection of catch and effort information on large pelagics also fulfills U.S. obligations to the International Commission for the Conservation of Atlantic Tunas (ICCAT).
The LPS includes two independent, yet complementary, surveys which provide the effort and average catch per trip estimates needed to estimate total catch by species. The Large Pelagics Intercept Survey (LPIS) is a dockside survey of fishing access sites, primarily designed to collect catch data from private and charterboat captains who have just completed fishing trips directed at large pelagic species. LPIS data are used to estimate the average recreational catch per large pelagic boat trip by species.
The LPIS involves intensive field interviewing in the coastal areas from Virginia through Maine.
In Maine, the LPIS is conducted by State personnel. QuanTech conducts the LPIS from Virginia through New Hampshire. The LPIS involves:
Revision and refinement of all field survey instruments and data collection procedures in cooperation with NOAA Fisheries;
Creation and maintenance of a sampling frame of large pelagic fishing access sites;
Detailed training of field interviewers in the methodology and procedures to be used in the field interviewing process; and,
Procedures to verify and enhance the quality of the data collected using comprehensive field management techniques, and in-house SAS data checking programs.
To meet the requirement of delivery of LPIS data files to NOAA Fisheries, data collected in the field is sent within 24 hours of interviewing assignment completion and checked for completeness and consistency. Optical Character Recognition (OCR) software is used to capture data from field forms. During data capture each entry on the form is verified by an OCR operator. A SAS dataset meeting NOAA Fisheries' specifications is prepared and delivered to NOAA Fisheries each month.
The Private vessel portion of the Large Pelagics Telephone Survey (LPTS) is conducted from QuanTech Headquarters in Rockville, Maryland using a custom-designed Computer Assisted Telephone Interviewing system. The LPTS collects data used to estimate the total number of boat trips on which anglers fished with rod and reel or handline for large pelagic species. For-hire boats are covered by a weekly survey, and private boats are covered by a biweekly survey. The Charter/Headboat LPTS is a survey of charter and headboat fishing for HMS. The Private LPTS covers both commercial fishing by vessels with General category HMS permits, and true recreational fishing by vessels with Angling category HMS permits.
3471 chars
SUB-PAGE (https://quantech.com/intercept/) In-Person Surveys – QuanTech Inc.
In-Person Surveys
QuanTech specializes in in-person intercept
surveys to collect various types of survey data. We have a network of experienced
field supervisors that oversee highly trained interviewing staff. Our interviewing
staff is trained on how to approach potential respondents in a manner that results
in a high level of participation; they are also trained to convert soft
refusals into participating respondents. Depending on our clients’ needs we collect
the data using two methods; paper survey responses and electronic field data
collection. Paper surveys are filled out by our
interviewers and sent to QuanTech's headquarters where advanced image
capturing software is used to convert handwritten responses into electronic
text which is then validated by our office staff. QuanTech is also using cutting edge computer assisted
personal interviewing systems to easily collect survey responses in the field.
QuanTech employs experienced programming staff to design, develop and program
electronic surveys that are deployed to laptops or sunlight readable tablets. Our
field staff are trained to use electronic devices to efficiently collect
responses from participants. A major benefit of electronic field data
collection is the ability to incorporate complex skip rules and error
checks that ensure the highest quality data is delivered to our clients in a timely
manner.
ProjectsFor additional information on our intercept surveys, please see:Large Pelagics SurveyLarge Pelagic Biological SurveyAnacostia River Creel Angler SurveyChesapeake Bay Blue Crab SurveyLower Passaic River Creel Angler SurveySocio-Economic Aspects Survey of Commercial Fishing Crew in the Northeast and Mid-AtlanticAmerican Healthy Homes Survey IIAmerican Healthy Homes Survey
1766 chars
🛡️ Trust Signals — reviews, proof links, trust-theatre flag (Trust & Proof)
4Review mentions (all pages)
0External proof links (all pages)
PageReviewsProof links
/ (home) 1 0
/lead-healthy-homes/ 1 0
/lps/ 1 0
/intercept/ 1 0
🔗 Identity & Technical Layer — schema JSON-LD: identity chains, entity gaps (Identity & Authority)
Homepage — no schema detected (entity gap)
/lead-healthy-homes/ — no schema detected (entity gap)
/lps/ — no schema detected (entity gap)
/intercept/ — no schema detected (entity gap)

Your Diagnosis

Before revealing the machine’s verdict, predict the BS score for each signal. Higher = more BS (more fluff, less verifiable substance). Drag each slider, then submit to compare your judgment against the engine.

Information Density 0 / 30
Read the Narrative & headings: do hard facts (prices, dates, numbers) outweigh fluff power-words?
Semantic Coherence 0 / 20
Compare the homepage promise against the sub-page reality. Do they hold the same line?
Trust & Proof 0 / 20
Weigh review mentions against actual external proof links. Claims without verification = theatre.
Commodity Fingerprint 0 / 15
Check headings & narrative against the industry clichés in the setup above.
Identity & Authority 0 / 15
Inspect the schema: is there real Organization/Person identity with sameAs links, or gaps?
Your predicted BS score 0 / 100
💡 Stuck? Reveal the heuristic lens — how the deterministic page-auditor reads each signal (no AI, pure pattern rules)

These are the structural rules a local, deterministic auditor applies — the same lens you can use to judge each signal. They describe what to look for, not this company’s result.

Information Density

Classify each sentence as substantive or hollow. Grounding markers — numbers, currencies, dates, technical units, named entities — outweigh marketing adjectives. When fluff sits right next to hard evidence, the fluff is forgiven.

Semantic Alignment

Pull the main entities out of the H1, then check whether they actually recur through the body. A page that announces one thing and then talks about another drifts. Headings with no real sentences underneath read as pseudo-substance.

Trust & Proof

Count trust words (review, testimonial, rating, verified) against real outbound proof links (Google, Trustpilot, Clutch, G2, Yelp). Lots of trust language with zero verification links is trust theatre. Unlinked logo galleries count against it.

Commodity Fingerprint

Look at how much sentence length varies. Natural writing varies its rhythm; templated or mass-produced copy is statistically uniform. Very low variation reads as commodity content — unless unique named entities break the pattern.

Identity & Authority

Inspect the JSON-LD. Is there an Organization or Person schema, and does it carry sameAs links to real external profiles (LinkedIn, socials)? Missing schema or no identity declaration signals an anonymous entity.

Want to apply this lens yourself? The free BS Indicator Chrome extension runs these heuristic checks live on any page. Bear in mind it is a single-page, deterministic tool — it relies only on pattern rules for the page in front of it and does not perform the cross-page semantic correlation this audit uses, so its readout is a starting lens, not the full verdict.

B
BS Level
Science, Research & Laboratories
34.3 Avg BS

Based on 126 businesses audited.

BS Detector

Science, Research & Laboratories BS: QuanTech Inc. (quantech.com)

https://quantech.com 📍 Industry: Science, Research & Laboratories
32 BS / 100

QuanTech is a legitimately substantive scientific contractor suffering from a severe technical credibility gap. The site’s content is authentic and detailed, but its digital architecture is neglected, resulting in a ‘Trust Theatre’ penalty that doesn’t reflect the high quality of its actual work.

Info Density Power-words vs. Substance ratio.
3
10% BS
Semantic Coherence Homepage promise vs. Sub-page reality.
4
20% BS
Trust & Proof Verifiable evidence vs. Trust Theatre.
11
55% BS
Commodity Fingerprint Detection of industry clichés/templates.
3
20% BS
Identity & Authority Expert verifiability & Schema depth.
11
73% BS

Immediately implement a standard heading hierarchy by adding an H1 to every page to match the primary signal. Add Person schema for Dr. Gary Dewalt and Dr. David Cox, including links to their publication records or professional profiles to close the authority gap. Replace the generic ‘review_count’ metadata with actual case study links or official performance evaluation (CPARS) references from federal clients. Update the meta_description tags to reflect the specific survey expertise instead of leaving them blank.

The content strongly confirms the classification as a scientific data collection and research firm. The text is saturated with specific methodologies like Computer Assisted Telephone Interviews (CATI) and Electronic Field Data Collection (EFDC) which are standard in high-level government survey contracting.

“The score of 32 represents a 'Low BS' profile. The score was kept low by the high specificity of the text and the absence of generic industry jargon. The points earned were primarily from technical failures (Identity and Authority) and the lack of verifiable external proof paths for their reviews and expert claims.”

Verified Analysis Date: June 19, 2026 © 1EuroSEO Independent Evaluator — Non-Sponsored Result