GOLDENWELL BIOTECH, INC.: gross profit
Gross profit for GOLDENWELL BIOTECH, INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.
All GOLDENWELL BIOTECH, INC. financial histories
What this measure means
Revenue less the costs directly attributed to the goods or services sold. It precedes other operating expenses and is not net income.
Exact concept: us-gaap:GrossProfit. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.
Coverage of this history
Selected reporting periods run from 2019-01-01 to 2025-12-31. The SEC response was captured on 2026-09-21.
Selected filing history
| Period start | Period end | Value | Unit | Filed | Source filing |
|---|---|---|---|---|---|
| 2025-01-01 | 2025-12-31 | 12 | USD | 2026-07-01 | 10-K · 0001477932-26-004130 |
| 2024-01-01 | 2024-12-31 | 64 | USD | 2026-07-01 | 10-K · 0001477932-26-004130 |
| 2023-01-01 | 2023-12-31 | 666 | USD | 2025-05-15 | 10-K · 0001477932-25-003784 |
| 2022-01-01 | 2022-12-31 | 25,186 | USD | 2024-04-12 | 10-K · 0001477932-24-002028 |
| 2021-01-01 | 2021-12-31 | 8,388 | USD | 2023-04-13 | 10-K · 0001477932-23-002478 |
| 2020-01-01 | 2020-12-31 | 0 | USD | 2023-02-06 | 10-K/A · 0001477932-23-000763 |
| 2019-01-01 | 2019-12-31 | 0 | USD | 2021-07-23 | 10-K · 0001477932-21-004870 |
Related financial histories
- GOLDENWELL BIOTECH, INC.: total assets
- GOLDENWELL BIOTECH, INC.: total liabilities
- GOLDENWELL BIOTECH, INC.: stockholders equity
- GOLDENWELL BIOTECH, INC.: cash and cash equivalents
- GOLDENWELL BIOTECH, INC.: net income or loss
- GOLDENWELL BIOTECH, INC.: operating cash flow
- GOLDENWELL BIOTECH, INC.: revenue
- GOLDENWELL BIOTECH, INC.: contract revenue excluding tax
- GOLDENWELL BIOTECH, INC.: financing cash flow
- GOLDENWELL BIOTECH, INC.: retained earnings or deficit
- GOLDENWELL BIOTECH, INC.: operating income or loss
- GOLDENWELL BIOTECH, INC.: interest expense
- GOLDENWELL BIOTECH, INC.: current liabilities
- GOLDENWELL BIOTECH, INC.: current accounts payable
- GOLDENWELL BIOTECH, INC.: operating expenses
- GOLDENWELL BIOTECH, INC.: net inventory
- GOLDENWELL BIOTECH, INC.: cost of revenue
- GOLDENWELL BIOTECH, INC.: selling, general and administrative expense
Inspect the source
- Entity
- GOLDENWELL BIOTECH, INC. / CIK 0001800373
- Captured
- 2026-09-21T17:27:56.460Z
- SEC response SHA-256
7f8aa3ca2a540d1a3c82b8dac24ca87c532e1b5913defe523f95a19c93661789
Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON
Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.
Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.
Use this in research
A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.
These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.
Research methodology · Execution and cost assumptions · Check backtest overfitting
Build with the open-source tools
Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.
- Get an API key and run your first validation
- Connect the MCP server to your coding assistant
- Inspect the ALPHAC engine on GitHub
- Read the MCP server source and integration examples
Read the published dataset with Python
import json
from urllib.request import urlopen
with urlopen("https://canlicapital.com/company-data/0001800373.json") as response:
record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
print(concept["tag"], next(iter(concept["observations"])))