PMC:7589389 / 33767-34512 JSONTXT

{"project":"LitCovid-PD-FMA-UBERON","denotations":[{"id":"T15","span":{"begin":33,"end":36},"obj":"Body_part"},{"id":"T16","span":{"begin":41,"end":44},"obj":"Body_part"},{"id":"T17","span":{"begin":557,"end":560},"obj":"Body_part"},{"id":"T18","span":{"begin":565,"end":568},"obj":"Body_part"}],"attributes":[{"id":"A15","pred":"fma_id","subj":"T15","obj":"http://purl.org/sig/ont/fma/fma84129"},{"id":"A16","pred":"fma_id","subj":"T16","obj":"http://purl.org/sig/ont/fma/fma84130"},{"id":"A17","pred":"fma_id","subj":"T17","obj":"http://purl.org/sig/ont/fma/fma84129"},{"id":"A18","pred":"fma_id","subj":"T18","obj":"http://purl.org/sig/ont/fma/fma84130"}],"text":"5.1. Research Design\nTo test the H2a and H2b, we generate the regression model as follows:CAR = β0 + β1CIPHT + β2CIPHT × Conditioning_VAR + β3Conditioning_VAR + β4PRO_CASE + β5SIZE + β6ROA + β7CURR + β8R\u0026D + β9LOSS + β10LEV + β11OPCF + β12TURN + β13CEO_AGE+ β14CEO_COM + β15CEO_TEN + β16CEO_DUA + Week FE + Industry FE + Province FE + ε(3) where Conditioning_VAR is a conditioning variable that moderates the association between continued increasing public health threats and accumulative abnormal return. All other variables are above-mentioned. To test H2a and H2b, Conditioning_VAR is in terms of the provincial information accessibility and provincial economic growth, respectively. We explain the detail proxies in the following sections."}

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T169","span":{"begin":24,"end":28},"obj":"http://purl.obolibrary.org/obo/UBERON_0000473"},{"id":"T170","span":{"begin":202,"end":205},"obj":"http://purl.obolibrary.org/obo/CLO_0008693"},{"id":"T171","span":{"begin":202,"end":205},"obj":"http://purl.obolibrary.org/obo/CLO_0008770"},{"id":"T172","span":{"begin":368,"end":369},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T173","span":{"begin":552,"end":556},"obj":"http://purl.obolibrary.org/obo/UBERON_0000473"}],"text":"5.1. Research Design\nTo test the H2a and H2b, we generate the regression model as follows:CAR = β0 + β1CIPHT + β2CIPHT × Conditioning_VAR + β3Conditioning_VAR + β4PRO_CASE + β5SIZE + β6ROA + β7CURR + β8R\u0026D + β9LOSS + β10LEV + β11OPCF + β12TURN + β13CEO_AGE+ β14CEO_COM + β15CEO_TEN + β16CEO_DUA + Week FE + Industry FE + Province FE + ε(3) where Conditioning_VAR is a conditioning variable that moderates the association between continued increasing public health threats and accumulative abnormal return. All other variables are above-mentioned. To test H2a and H2b, Conditioning_VAR is in terms of the provincial information accessibility and provincial economic growth, respectively. We explain the detail proxies in the following sections."}

{"project":"LitCovid-PD-CHEBI","denotations":[{"id":"T18","span":{"begin":303,"end":305},"obj":"Chemical"},{"id":"T19","span":{"begin":317,"end":319},"obj":"Chemical"},{"id":"T20","span":{"begin":331,"end":333},"obj":"Chemical"}],"attributes":[{"id":"A18","pred":"chebi_id","subj":"T18","obj":"http://purl.obolibrary.org/obo/CHEBI_74712"},{"id":"A19","pred":"chebi_id","subj":"T19","obj":"http://purl.obolibrary.org/obo/CHEBI_74712"},{"id":"A20","pred":"chebi_id","subj":"T20","obj":"http://purl.obolibrary.org/obo/CHEBI_74712"}],"text":"5.1. Research Design\nTo test the H2a and H2b, we generate the regression model as follows:CAR = β0 + β1CIPHT + β2CIPHT × Conditioning_VAR + β3Conditioning_VAR + β4PRO_CASE + β5SIZE + β6ROA + β7CURR + β8R\u0026D + β9LOSS + β10LEV + β11OPCF + β12TURN + β13CEO_AGE+ β14CEO_COM + β15CEO_TEN + β16CEO_DUA + Week FE + Industry FE + Province FE + ε(3) where Conditioning_VAR is a conditioning variable that moderates the association between continued increasing public health threats and accumulative abnormal return. All other variables are above-mentioned. To test H2a and H2b, Conditioning_VAR is in terms of the provincial information accessibility and provincial economic growth, respectively. We explain the detail proxies in the following sections."}

{"project":"LitCovid-PD-GO-BP","denotations":[{"id":"T11","span":{"begin":667,"end":673},"obj":"http://purl.obolibrary.org/obo/GO_0040007"}],"text":"5.1. Research Design\nTo test the H2a and H2b, we generate the regression model as follows:CAR = β0 + β1CIPHT + β2CIPHT × Conditioning_VAR + β3Conditioning_VAR + β4PRO_CASE + β5SIZE + β6ROA + β7CURR + β8R\u0026D + β9LOSS + β10LEV + β11OPCF + β12TURN + β13CEO_AGE+ β14CEO_COM + β15CEO_TEN + β16CEO_DUA + Week FE + Industry FE + Province FE + ε(3) where Conditioning_VAR is a conditioning variable that moderates the association between continued increasing public health threats and accumulative abnormal return. All other variables are above-mentioned. To test H2a and H2b, Conditioning_VAR is in terms of the provincial information accessibility and provincial economic growth, respectively. We explain the detail proxies in the following sections."}

{"project":"LitCovid-sentences","denotations":[{"id":"T244","span":{"begin":0,"end":4},"obj":"Sentence"},{"id":"T245","span":{"begin":5,"end":20},"obj":"Sentence"},{"id":"T246","span":{"begin":21,"end":507},"obj":"Sentence"},{"id":"T247","span":{"begin":508,"end":548},"obj":"Sentence"},{"id":"T248","span":{"begin":549,"end":688},"obj":"Sentence"},{"id":"T249","span":{"begin":689,"end":745},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"5.1. Research Design\nTo test the H2a and H2b, we generate the regression model as follows:CAR = β0 + β1CIPHT + β2CIPHT × Conditioning_VAR + β3Conditioning_VAR + β4PRO_CASE + β5SIZE + β6ROA + β7CURR + β8R\u0026D + β9LOSS + β10LEV + β11OPCF + β12TURN + β13CEO_AGE+ β14CEO_COM + β15CEO_TEN + β16CEO_DUA + Week FE + Industry FE + Province FE + ε(3) where Conditioning_VAR is a conditioning variable that moderates the association between continued increasing public health threats and accumulative abnormal return. All other variables are above-mentioned. To test H2a and H2b, Conditioning_VAR is in terms of the provincial information accessibility and provincial economic growth, respectively. We explain the detail proxies in the following sections."}

{"project":"LitCovid-PubTator","denotations":[{"id":"218","span":{"begin":41,"end":44},"obj":"Gene"},{"id":"219","span":{"begin":565,"end":568},"obj":"Gene"},{"id":"220","span":{"begin":33,"end":36},"obj":"Gene"},{"id":"221","span":{"begin":557,"end":560},"obj":"Gene"}],"attributes":[{"id":"A218","pred":"tao:has_database_id","subj":"218","obj":"Gene:8349"},{"id":"A219","pred":"tao:has_database_id","subj":"219","obj":"Gene:8349"},{"id":"A220","pred":"tao:has_database_id","subj":"220","obj":"Gene:113457"},{"id":"A221","pred":"tao:has_database_id","subj":"221","obj":"Gene:113457"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"5.1. Research Design\nTo test the H2a and H2b, we generate the regression model as follows:CAR = β0 + β1CIPHT + β2CIPHT × Conditioning_VAR + β3Conditioning_VAR + β4PRO_CASE + β5SIZE + β6ROA + β7CURR + β8R\u0026D + β9LOSS + β10LEV + β11OPCF + β12TURN + β13CEO_AGE+ β14CEO_COM + β15CEO_TEN + β16CEO_DUA + Week FE + Industry FE + Province FE + ε(3) where Conditioning_VAR is a conditioning variable that moderates the association between continued increasing public health threats and accumulative abnormal return. All other variables are above-mentioned. To test H2a and H2b, Conditioning_VAR is in terms of the provincial information accessibility and provincial economic growth, respectively. We explain the detail proxies in the following sections."}