NonprofitMedical research institutesDenmark
Danish Cancer Society is a nonprofit in medical research institutes founded in 1928[1] and based in Copenhagen, Denmark[1].
Each with its fit to Danish Cancer Society, from 0 to 100%: how close it is in what it does, its industry, the distinctive parts both public maps hold, and size and region. 85% and above is a direct peer, 70 to 85 close, 60 to 70 related; under 65 is left out, so there may be few. Open a row for its breakdown.
Nonprofit · Medical research institutes · Sweden
| Component | Match | Weight | Adds |
|---|---|---|---|
| What it doesHow close its public description reads to Danish Cancer Society's, against an ordinary organization. | 89% | 61% | +54.6 |
| IndustrySame segment | 73% | 33% | +24.4 |
| Shared partsNeeds a public map on both sides: left out. | n/a | — | — |
| Size & regionCountry different · size not known for both · model not known for both. | 0% | 6% | +0.0 |
| Fit | 79% | ||
Fit = Σ weight × match over the components known for both, the weights re-scaled to 100%. Unknown is left out, never counted as a difference.
Nonprofit · Medical research institutes · Denmark
| Component | Match | Weight | Adds |
|---|---|---|---|
| What it doesHow close its public description reads to Danish Cancer Society's, against an ordinary organization. | 77% | 61% | +47.2 |
| IndustrySame segment | 73% | 33% | +24.4 |
| Shared partsNeeds a public map on both sides: left out. | n/a | — | — |
| Size & regionCountry same · size not known for both · model not known for both. | 100% | 6% | +5.6 |
| Fit | 77% | ||
Fit = Σ weight × match over the components known for both, the weights re-scaled to 100%. Unknown is left out, never counted as a difference.
Nonprofit · Medical research institutes · Germany
| Component | Match | Weight | Adds |
|---|---|---|---|
| What it doesHow close its public description reads to Danish Cancer Society's, against an ordinary organization. | 83% | 61% | +50.7 |
| IndustrySame segment | 73% | 33% | +24.4 |
| Shared partsNeeds a public map on both sides: left out. | n/a | — | — |
| Size & regionCountry different · size not known for both · model not known for both. | 0% | 6% | +0.0 |
| Fit | 75% | ||
Fit = Σ weight × match over the components known for both, the weights re-scaled to 100%. Unknown is left out, never counted as a difference.
Nonprofit · Medical research institutes · Denmark
| Component | Match | Weight | Adds |
|---|---|---|---|
| What it doesHow close its public description reads to Danish Cancer Society's, against an ordinary organization. | 72% | 61% | +44.2 |
| IndustrySame segment | 73% | 33% | +24.4 |
| Shared partsNeeds a public map on both sides: left out. | n/a | — | — |
| Size & regionCountry same · size not known for both · model not known for both. | 100% | 6% | +5.6 |
| Fit | 74% | ||
Fit = Σ weight × match over the components known for both, the weights re-scaled to 100%. Unknown is left out, never counted as a difference.
Nonprofit · Medical research institutes · South Korea
| Component | Match | Weight | Adds |
|---|---|---|---|
| What it doesHow close its public description reads to Danish Cancer Society's, against an ordinary organization. | 78% | 61% | +47.8 |
| IndustrySame segment | 73% | 33% | +24.4 |
| Shared partsNeeds a public map on both sides: left out. | n/a | — | — |
| Size & regionCountry different · size not known for both · model not known for both. | 0% | 6% | +0.0 |
| Fit | 72% | ||
Fit = Σ weight × match over the components known for both, the weights re-scaled to 100%. Unknown is left out, never counted as a difference.
Nonprofit · Medical research institutes · Japan
| Component | Match | Weight | Adds |
|---|---|---|---|
| What it doesHow close its public description reads to Danish Cancer Society's, against an ordinary organization. | 75% | 61% | +46.1 |
| IndustrySame segment | 73% | 33% | +24.4 |
| Shared partsNeeds a public map on both sides: left out. | n/a | — | — |
| Size & regionCountry different · size not known for both · model not known for both. | 0% | 6% | +0.0 |
| Fit | 70% | ||
Fit = Σ weight × match over the components known for both, the weights re-scaled to 100%. Unknown is left out, never counted as a difference.
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