lack of prediction

USAGE SUMMARY

The phrase "lack of prediction" is correct and usable in written English.
It can be used to describe a situation where there is an absence of foresight or the ability to anticipate future events. Example: "The lack of prediction in the market trends has left investors uncertain about their next moves."

✓ Grammatically correct

Science

News & Media

Formal & Business

Human-verified examples from authoritative sources

Exact Expressions

16 human-written examples

They help us predict our lack of prediction.

Forbes

This result can be explained by the lack of prediction capabilities of β-presumed pdf in weakly turbulent flow with a coarse mesh resolution, as shown in the first part of this work.

Combustion and Flame

However, because of the lack of prediction capability of pavement skid resistance under various rainfall intensities, the minimum skid resistance threshold for safe wet-weather driving has been specified by highway agencies based on either engineering judgement or past experience.

International Journal of Transportation Science and Technology

The main weak points in using AI optimization technique are the possibility of being trapped at local minima, being confined to the population space, difficulty to solve heavily nonlinear problems and to make full use of the historical information beside the lack of prediction about the search space.

Ain Shams Engineering Journal

Some issues are known relative to this lack of prediction.

BioData Mining

There are a number of reasons for this lack of prediction.

BMC Medical Ethics

Human-verified similar examples from authoritative sources

Similar Expressions

44 human-written examples

The negative bias was primarily because of the underestimation in high biomass ranges and lack of predictions in non-forested areas.

Carbon Balance and Management

Loop quantum gravity is seemingly less plagued by a lack of predictions, and indeed it is often claimed that the discreteness of area and volume operators are concrete predictions of the theory, with potentially testable consequences.

SEP

Examination of the genes which comprise the PB signatures of partial body irradiation provide a possible explanation for the lack of predictions across different partial irradiation conditions.

Plosone

To illustrate the performance of the clustering technique, and perhaps an explanation for the lack of predictions with the reduced set, we highlight two cluster sets from a single target, Dopamine D4.

Database : the journal of biological databases and curation

Evidently "positive prediction" means the prediction of a PEP-promoter and "negative prediction" means the lack of positive prediction.

Biology Direct

Expert writing Tips

Best practice

When discussing the "lack of prediction" in a specific field or model, clearly identify what aspects are difficult to predict and the potential consequences of this uncertainty.

Common error

Avoid suggesting that something is completely unpredictable when there may be some factors that can be partially predicted. Instead, acknowledge the "lack of prediction" while recognizing any existing trends or data that offer limited insights.

Linguistic Context

The phrase "lack of prediction" functions primarily as a noun phrase. It typically serves as the subject or object of a sentence, describing an absence or deficiency in the ability to forecast or anticipate future events. Ludwig confirms the correctness and usability of this phrase.

Expression frequency: Uncommon

Frequent in

Science

50%

News & Media

25%

Formal & Business

25%

Less common in

Wiki

0%

Reference

0%

Social Media

0%

Ludwig's WRAP-UP

The phrase "lack of prediction" is a grammatically sound and useful term for describing situations where forecasting is limited or absent. Ludwig AI validates its correctness. Its primary function is to identify limitations in different scenarios, mostly in science, news and formal business contexts. While alternatives like "unpredictability" or "absence of forecasting" exist, "lack of prediction" specifically focuses on the deficiency in the act of predicting. Remember to use it precisely, avoiding overstatements about the complete impossibility of forecasting when some partial insights might still exist.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

unpredictability

Focuses on the inherent inability to foresee outcomes.

absence of forecasting

Highlights the non-existence of any predictive analysis.

inability to foresee

Emphasizes the incapacity to anticipate future events.

foresight deficiency

Directly points out the shortage of anticipation skills.

failure to anticipate

Stresses the unsuccessful attempts to foresee.

no anticipation

Simply states the absence of forethought.

poor prognostic capability

Indicates a low level of skill in predicting outcomes.

limited predictability

Suggests that only some things can be predicted.

deficient anticipation

Highlights that anticipation is not well executed.

scarcity of foresight

Emphasizes the limited availability of forward-thinking.

FAQs

How can I use "lack of prediction" in a sentence?

You can use "lack of prediction" to describe situations where forecasting future outcomes is difficult or impossible. For example, "The "lack of prediction" in climate models makes long-term planning challenging."

What are some alternatives to "lack of prediction"?

Alternatives include "unpredictability", "absence of forecasting", or "inability to foresee", depending on the specific context you want to convey.

Is it better to say "lack of prediction" or "lack of predictions"?

"Lack of prediction" refers to a general absence of predictive capability, while "lack of predictions" refers to a specific absence of forecasted outcomes or estimations. The better choice depends on the intended meaning.

What does it mean when there is a "lack of prediction" in a scientific model?

It means that the model has limited ability to accurately forecast future states or outcomes based on the available data and parameters. This could be due to inherent complexity, incomplete data, or limitations in the model's design.