The lecture disputes the idea presented in the reading passage about the effectiveness of cloud seeding in preventing damage to crops caused by formation of hail. The lecturer asserts that cloud seeding does not work in all geographic areas and may cause crops to die due to other reasons.
First of all the lecturer believes that cloud seeding may cause drought. The reading states that in laboratory experiments cloud seeding changed hail into snow. However, the lecturer states that with cloud seeding, there was a reduction in hail, snow, and rain. Thus, in real life using this approach to prevent hail formation may cause crops to die because of dryness and lack of water.
The lecturer also states that we cannot generalize the effectiveness of this approach in all region. The author states that this approach was effective in reducing hail in Asia, However, The lecturer states that this same procedure may not hold true in some other regions. For example,in the US, the air is less polluted which can explain why cloud seeding is not effective. He argues that pollutant particle in Asia may have interacted with silver iodide and cause a reduction in hail.
Finally the lecturer argues that in local studies we observed less crops damage in vast geographic areas. According to the lecturer, this might not be due solely to a reduction in hail, but there might be other natural factors that have contributed to the protection of crop, such as the use of fertilizers or pesticides.
Grammar and spelling errors:
Line 5, column 285, Rule ID: COMMA_PARENTHESIS_WHITESPACE
Message: Put a space after the comma
Suggestion: , in
... true in some other regions. For example,in the US, the air is less polluted which ...
^^^
Line 7, column 1, Rule ID: SENT_START_CONJUNCTIVE_LINKING_ADVERB_COMMA[1]
Message: Did you forget a comma after a conjunctive/linking adverb?
Suggestion: Finally,
...odide and cause a reduction in hail. Finally the lecturer argues that in local studi...
^^^^^^^
Transition Words or Phrases used:
also, but, finally, first, however, if, may, so, thus, for example, such as, first of all
Attributes: Values AverageValues Percentages(Values/AverageValues)% => Comments
Performance on Part of Speech:
To be verbs : 6.0 10.4613686534 57% => More to be verbs wanted.
Auxiliary verbs: 9.0 5.04856512141 178% => OK
Conjunction : 6.0 7.30242825607 82% => OK
Relative clauses : 11.0 12.0772626932 91% => OK
Pronoun: 19.0 22.412803532 85% => OK
Preposition: 37.0 30.3222958057 122% => OK
Nominalization: 6.0 5.01324503311 120% => OK
Performance on vocabulary words:
No of characters: 1250.0 1373.03311258 91% => OK
No of words: 251.0 270.72406181 93% => More content wanted.
Chars per words: 4.98007968127 5.08290768461 98% => OK
Fourth root words length: 3.98032404683 4.04702891845 98% => OK
Word Length SD: 2.52600952403 2.5805825403 98% => OK
Unique words: 127.0 145.348785872 87% => More unique words wanted.
Unique words percentage: 0.505976095618 0.540411800872 94% => More unique words wanted or less content wanted.
syllable_count: 380.7 419.366225166 91% => OK
avg_syllables_per_word: 1.5 1.55342163355 97% => OK
A sentence (or a clause, phrase) starts by:
Pronoun: 2.0 3.25607064018 61% => OK
Article: 8.0 8.23620309051 97% => OK
Subordination: 0.0 1.25165562914 0% => More adverbial clause wanted.
Conjunction: 2.0 1.51434878587 132% => OK
Preposition: 3.0 2.5761589404 116% => OK
Performance on sentences:
How many sentences: 12.0 13.0662251656 92% => OK
Sentence length: 20.0 21.2450331126 94% => OK
Sentence length SD: 38.953943603 49.2860985944 79% => OK
Chars per sentence: 104.166666667 110.228320801 95% => OK
Words per sentence: 20.9166666667 21.698381199 96% => OK
Discourse Markers: 7.41666666667 7.06452816374 105% => OK
Paragraphs: 4.0 4.09492273731 98% => OK
Language errors: 2.0 4.19205298013 48% => OK
Sentences with positive sentiment : 4.0 4.33554083885 92% => OK
Sentences with negative sentiment : 6.0 4.45695364238 135% => OK
Sentences with neutral sentiment: 2.0 4.27373068433 47% => OK
What are sentences with positive/Negative/neutral sentiment?
Coherence and Cohesion:
Essay topic to essay body coherence: 0.0757493139299 0.272083759551 28% => The similarity between the topic and the content is low.
Sentence topic coherence: 0.0333494543461 0.0996497079465 33% => Sentence topic similarity is low.
Sentence topic coherence SD: 0.0170258643856 0.0662205650399 26% => Sentences are similar to each other.
Paragraph topic coherence: 0.0526124422434 0.162205337803 32% => Maybe some paragraphs are off the topic.
Paragraph topic coherence SD: 0.0150720507322 0.0443174109184 34% => Paragraphs are similar to each other. Some content may get duplicated or it is not exactly right on the topic.
Essay readability:
automated_readability_index: 12.5 13.3589403974 94% => Automated_readability_index is low.
flesch_reading_ease: 59.64 53.8541721854 111% => OK
smog_index: 3.1 5.55761589404 56% => Smog_index is low.
flesch_kincaid_grade: 9.9 11.0289183223 90% => OK
coleman_liau_index: 11.6 12.2367328918 95% => OK
dale_chall_readability_score: 8.21 8.42419426049 97% => OK
difficult_words: 57.0 63.6247240618 90% => OK
linsear_write_formula: 8.0 10.7273730684 75% => OK
gunning_fog: 10.0 10.498013245 95% => OK
text_standard: 10.0 11.2008830022 89% => OK
What are above readability scores?
---------------------
It is not exactly right on the topic in the view of e-grader. Maybe there is a wrong essay topic.
Rates: 3.33333333333 out of 100
Scores by essay e-grader: 1.0 Out of 30
---------------------
Note: the e-grader does NOT examine the meaning of words and ideas. VIP users will receive further evaluations by advanced module of e-grader and human graders.